Search results for: histopathological image
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3056

Search results for: histopathological image

2696 Least Support Orthogonal Matching Pursuit (LS-OMP) Recovery Method for Invisible Watermarking Image

Authors: Israa Sh. Tawfic, Sema Koc Kayhan

Abstract:

In this paper, first, we propose least support orthogonal matching pursuit (LS-OMP) algorithm to improve the performance, of the OMP (orthogonal matching pursuit) algorithm. LS-OMP algorithm adaptively chooses optimum L (least part of support), at each iteration. This modification helps to reduce the computational complexity significantly and performs better than OMP algorithm. Second, we give the procedure for the invisible image watermarking in the presence of compressive sampling. The image reconstruction based on a set of watermarked measurements is performed using LS-OMP.

Keywords: compressed sensing, orthogonal matching pursuit, restricted isometry property, signal reconstruction, least support orthogonal matching pursuit, watermark

Procedia PDF Downloads 338
2695 Steel Bridge Coating Inspection Using Image Processing with Neural Network Approach

Authors: Ahmed Elbeheri, Tarek Zayed

Abstract:

Steel bridges deterioration has been one of the problems in North America for the last years. Steel bridges deterioration mainly attributed to the difficult weather conditions. Steel bridges suffer fatigue cracks and corrosion, which necessitate immediate inspection. Visual inspection is the most common technique for steel bridges inspection, but it depends on the inspector experience, conditions, and work environment. So many Non-destructive Evaluation (NDE) models have been developed use Non-destructive technologies to be more accurate, reliable and non-human dependent. Non-destructive techniques such as The Eddy Current Method, The Radiographic Method (RT), Ultra-Sonic Method (UT), Infra-red thermography and Laser technology have been used. Digital Image processing will be used for Corrosion detection as an Alternative for visual inspection. Different models had used grey-level and colored digital image for processing. However, color image proved to be better as it uses the color of the rust to distinguish it from the different backgrounds. The detection of the rust is an important process as it’s the first warning for the corrosion and a sign of coating erosion. To decide which is the steel element to be repainted and how urgent it is the percentage of rust should be calculated. In this paper, an image processing approach will be developed to detect corrosion and its severity. Two models were developed 1st to detect rust and 2nd to detect rust percentage.

Keywords: steel bridge, bridge inspection, steel corrosion, image processing

Procedia PDF Downloads 306
2694 Nephroprotective Effect of Aqueous Extract of Plectranthus amboinicus (Roxb.) Leaves in Adriamycin Induced Acute Renal Failure in Wistar Rats: A Biochemical and Histopathological Assessment

Authors: Ampe Mohottige Sachinthi Sandaruwani Amarasiri, Anoja Priyadarshani Attanayake, Kamani Ayoma Perera Wijewardana Jayatilaka, Lakmini Kumari Boralugoda Mudduwa

Abstract:

The search for alternative pharmacological therapies based on natural extracts for renal failure has become an urgent need, due to paucity of effective pharmacotherapy. The current study was undertaken to evaluate the acute nephroprotective effect of aqueous leaf extract of Plectranthus amboinicus (Roxb.) (Family: Lamiaceae), a medicinal plant used in traditional Ayurvedic medicine for the management of renal diseases in Sri Lanka. The study was performed in adriamycin (ADR) induced nephrotoxic in Wistar rats. Wistar rats were randomly divided into four groups each with six rats. A single dose of ADR (20 mg/kg body wt., ip) was used for the induction of nephrotoxicity in all groups of rats except group one. The treatments were started 24 hours after induction of nephrotoxicity and continued for three days. Group one and two served as healthy and nephrotoxic control rats and were administered equivalent volumes of normal saline (0.9% NaCl) orally. Group three and four nephrotoxic rats were administered the lyophilized powder of the aqueous extract of P. amboinicus (400 mg/ kg body wt.; equivalent human therapeutic dose) and the standard drug, fosinopril sodium (0.09 mg/ kg body wt.) respectively. Urine and blood samples were collected from rats in each group at the end of the period of intervention for the estimation of selected renal parameters. H and E stained sections of the kidney tissues were examined for histopathological changes. Rats treated with the plant extract showed significant improvement in biochemical parameters and histopathological changes compared to ADR induced nephrotoxic group. The elevation of serum concentrations of creatinine and β2-microglobulin were decreased by 38%, and 66% in plant extract treated nephrotoxic rats respectively (p < 0.05). In addition, serum concentrations of total protein and albumin were significantly increased by 25% and 14% in rats treated with P. amboinicus respectively (p < 0.05). The results of β2 –microglobulin and serum total protein demonstrated a significant reduction in the elevated values in rats administered with the plant extract (400 mg/kg) compared to that of fosinopril (0.09 mg/kg). Urinary protein loss in 24hr urine samples was significantly decreased in rats treated with both fosinopril (86%) and P. ambonicus (56%) at the end of the intervention (p < 0.01). Accordingly, an attenuation of morphological destruction was observed in the H and E stained sections of the kidney with the treatments of plant extract and fosinopril. The results of the present study revealed that the aqueous leaf extract of P. amboinicus possesses significant nephroprotective activity at the equivalent therapeutic dose of 400 mg/ kg against adriamycin induced acute nephrotoxicity.

Keywords: biochemical assessment, histopathological assessment, nephroprotective activity, Plectranthus amboinicus

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2693 Exploring the Representations of the Moroccan Female Body on Social Media: YouTube as a Case Study

Authors: Nadir Akrachi

Abstract:

YouTube is one of the social media platforms that has gained popularity over the last decade. With the use of YouTube channels, young girls are able to post videos about their opinions of the ideal body and beauty and connect to their audience through likes, comments, and shares. In addition, it has become apparent that these young women associate their bodies with the ideal body image. They relate their body to the ideal body aspects that are produced by YouTubers, which causes differences between their body shape and the ideal body. Thus, this has led many researchers to explore whether these social media outlets are influencing the ways women look at their bodies and whether these social media associations cause a negative body image. The purpose of the study is to examine body image perceptions of Moroccan YouTubers. In other words, the study will explore the ways Moroccan YouTubers perceive their body and whether they follow a pattern of objectification or not.

Keywords: body image, gender, social media, representation, female body

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2692 Automatic Vehicle Detection Using Circular Synthetic Aperture Radar Image

Authors: Leping Chen, Daoxiang An, Xiaotao Huang

Abstract:

Automatic vehicle detection using synthetic aperture radar (SAR) image has been widely researched, as well as using optical remote sensing images. However, most researches treat the detection as an independent problem, failing to make full use of SAR data information. In circular SAR (CSAR), the two long borders of vehicle will shrink if the imaging surface is set higher than the reference one. Based on above variance, an automatic vehicle detection using CSAR image is proposed to enhance detection ability under complex environment, such as vehicles’ closely packing, which confuses the detector. The detection method uses the multiple images generated by different height plane to obtain an energy-concentrated image for detecting and then uses the maximally stable extremal regions method (MSER) to detect vehicles. A result of vehicles’ detection is given to verify the effectiveness and correctness of proposed method.

Keywords: circular SAR, vehicle detection, automatic, imaging

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2691 Design and Development of 5-DOF Color Sorting Manipulator for Industrial Applications

Authors: Atef A. Ata, Sohair F. Rezeka, Ahmed El-Shenawy, Mohammed Diab

Abstract:

Image processing in today’s world grabs massive attentions as it leads to possibilities of broaden application in many fields of high technology. The real challenge is how to improve existing sorting system applications which consists of two integrated stations of processing and handling with a new image processing feature. Existing color sorting techniques use a set of inductive, capacitive, and optical sensors to differentiate object color. This research presents a mechatronics color sorting system solution with the application of image processing. A 5-DOF robot arm is designed and developed with pick and place operation to be main part of the color sorting system. Image processing procedure senses the circular objects in an image captured in real time by a webcam attached at the end-effector then extracts color and position information out of it. This information is passed as a sequence of sorting commands to the manipulator that has pick-and-place mechanism. Performance analysis proves that this color based object sorting system works very accurate under ideal condition in term of adequate illumination, circular objects shape and color. The circular objects tested for sorting are red, green and blue. For non-ideal condition, such as unspecified color the accuracy reduces to 80%.

Keywords: robotics manipulator, 5-DOF manipulator, image processing, color sorting, pick-and-place

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2690 Multiple Fusion Based Single Image Dehazing

Authors: Joe Amalraj, M. Arunkumar

Abstract:

Haze is an atmospheric phenomenon that signicantly degrades the visibility of outdoor scenes. This is mainly due to the atmosphere particles that absorb and scatter the light. This paper introduces a novel single image approach that enhances the visibility of such degraded images. In this method is a fusion-based strategy that derives from two original hazy image inputs by applying a white balance and a contrast enhancing procedure. To blend effectively the information of the derived inputs to preserve the regions with good visibility, we filter their important features by computing three measures (weight maps): luminance, chromaticity, and saliency. To minimize artifacts introduced by the weight maps, our approach is designed in a multiscale fashion, using a Laplacian pyramid representation. This paper demonstrates the utility and effectiveness of a fusion-based technique for de-hazing based on a single degraded image. The method performs in a per-pixel fashion, which is straightforward to implement. The experimental results demonstrate that the method yields results comparative to and even better than the more complex state-of-the-art techniques, having the advantage of being appropriate for real-time applications.

Keywords: single image de-hazing, outdoor images, enhancing, DSP

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2689 Implementation and Performance Analysis of Data Encryption Standard and RSA Algorithm with Image Steganography and Audio Steganography

Authors: S. C. Sharma, Ankit Gambhir, Rajeev Arya

Abstract:

In today’s era data security is an important concern and most demanding issues because it is essential for people using online banking, e-shopping, reservations etc. The two major techniques that are used for secure communication are Cryptography and Steganography. Cryptographic algorithms scramble the data so that intruder will not able to retrieve it; however steganography covers that data in some cover file so that presence of communication is hidden. This paper presents the implementation of Ron Rivest, Adi Shamir, and Leonard Adleman (RSA) Algorithm with Image and Audio Steganography and Data Encryption Standard (DES) Algorithm with Image and Audio Steganography. The coding for both the algorithms have been done using MATLAB and its observed that these techniques performed better than individual techniques. The risk of unauthorized access is alleviated up to a certain extent by using these techniques. These techniques could be used in Banks, RAW agencies etc, where highly confidential data is transferred. Finally, the comparisons of such two techniques are also given in tabular forms.

Keywords: audio steganography, data security, DES, image steganography, intruder, RSA, steganography

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2688 A Picture is worth a Billion Bits: Real-Time Image Reconstruction from Dense Binary Pixels

Authors: Tal Remez, Or Litany, Alex Bronstein

Abstract:

The pursuit of smaller pixel sizes at ever increasing resolution in digital image sensors is mainly driven by the stringent price and form-factor requirements of sensors and optics in the cellular phone market. Recently, Eric Fossum proposed a novel concept of an image sensor with dense sub-diffraction limit one-bit pixels (jots), which can be considered a digital emulation of silver halide photographic film. This idea has been recently embodied as the EPFL Gigavision camera. A major bottleneck in the design of such sensors is the image reconstruction process, producing a continuous high dynamic range image from oversampled binary measurements. The extreme quantization of the Poisson statistics is incompatible with the assumptions of most standard image processing and enhancement frameworks. The recently proposed maximum-likelihood (ML) approach addresses this difficulty, but suffers from image artifacts and has impractically high computational complexity. In this work, we study a variant of a sensor with binary threshold pixels and propose a reconstruction algorithm combining an ML data fitting term with a sparse synthesis prior. We also show an efficient hardware-friendly real-time approximation of this inverse operator. Promising results are shown on synthetic data as well as on HDR data emulated using multiple exposures of a regular CMOS sensor.

Keywords: binary pixels, maximum likelihood, neural networks, sparse coding

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2687 Using A Corpus Approach To Investigate Positive University Images: A Comparison Between Chinese And ESC Universities

Authors: Han Hongmei

Abstract:

University image is receiving attention because of its key role in influencing student choice, faculty loyalty, and social recognition. Therefore, all universities strive to promote their positive images. However, for most people, the positive image of a university is often from fragmented perceptual understanding. Since universities’ official websites are important channels for image promotion, a corpus approach to university profiles in their official websites can reveal holistic positive images of universities. This study aims to compare positive images of high-level universities in China and English-speaking countries based on a profile corpus of theseuniversities. It is found that the positive images revealed in these university profiles are similar, with some minor differences. The similarities are reflected in the campus environment, historical achievements, comprehensive characteristics, scientific research institutions, and diversified faculty; while the differences are reflected in their unique characteristics. Furthermore, the findings also reveal a gap between Chinese universities and high-level universities in the English-speaking countries.

Keywords: university image, positive image, corpus of university profiles, comparative analysis, high-frequency words

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2686 DWT-SATS Based Detection of Image Region Cloning

Authors: Michael Zimba

Abstract:

A duplicated image region may be subjected to a number of attacks such as noise addition, compression, reflection, rotation, and scaling with the intention of either merely mating it to its targeted neighborhood or preventing its detection. In this paper, we present an effective and robust method of detecting duplicated regions inclusive of those affected by the various attacks. In order to reduce the dimension of the image, the proposed algorithm firstly performs discrete wavelet transform, DWT, of a suspicious image. However, unlike most existing copy move image forgery (CMIF) detection algorithms operating in the DWT domain which extract only the low frequency sub-band of the DWT of the suspicious image thereby leaving valuable information in the other three sub-bands, the proposed algorithm simultaneously extracts features from all the four sub-bands. The extracted features are not only more accurate representation of image regions but also robust to additive noise, JPEG compression, and affine transformation. Furthermore, principal component analysis-eigenvalue decomposition, PCA-EVD, is applied to reduce the dimension of the features. The extracted features are then sorted using the more computationally efficient Radix Sort algorithm. Finally, same affine transformation selection, SATS, a duplication verification method, is applied to detect duplicated regions. The proposed algorithm is not only fast but also more robust to attacks compared to the related CMIF detection algorithms. The experimental results show high detection rates.

Keywords: affine transformation, discrete wavelet transform, radix sort, SATS

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2685 A Hybrid Watermarking Scheme Using Discrete and Discrete Stationary Wavelet Transformation For Color Images

Authors: Bülent Kantar, Numan Ünaldı

Abstract:

This paper presents a new method which includes robust and invisible digital watermarking on images that is colored. Colored images are used as watermark. Frequency region is used for digital watermarking. Discrete wavelet transform and discrete stationary wavelet transform are used for frequency region transformation. Low, medium and high frequency coefficients are obtained by applying the two-level discrete wavelet transform to the original image. Low frequency coefficients are obtained by applying one level discrete stationary wavelet transform separately to all frequency coefficient of the two-level discrete wavelet transformation of the original image. For every low frequency coefficient obtained from one level discrete stationary wavelet transformation, watermarks are added. Watermarks are added to all frequency coefficients of two-level discrete wavelet transform. Totally, four watermarks are added to original image. In order to get back the watermark, the original and watermarked images are applied with two-level discrete wavelet transform and one level discrete stationary wavelet transform. The watermark is obtained from difference of the discrete stationary wavelet transform of the low frequency coefficients. A total of four watermarks are obtained from all frequency of two-level discrete wavelet transform. Obtained watermark results are compared with real watermark results, and a similarity result is obtained. A watermark is obtained from the highest similarity values. Proposed methods of watermarking are tested against attacks of the geometric and image processing. The results show that proposed watermarking method is robust and invisible. All features of frequencies of two level discrete wavelet transform watermarking are combined to get back the watermark from the watermarked image. Watermarks have been added to the image by converting the binary image. These operations provide us with better results in getting back the watermark from watermarked image by attacking of the geometric and image processing.

Keywords: watermarking, DWT, DSWT, copy right protection, RGB

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2684 A Way of Converting Color Images to Gray Scale Ones for the Color-Blind: Applying to the part of the Tokyo Subway Map

Authors: Katsuhiro Narikiyo, Shota Hashikawa

Abstract:

This paper proposes a way of removing noises and reducing the number of colors contained in a JPEG image. Main purpose of this project is to convert color images to monochrome images for the color-blind. We treat the crispy color images like the Tokyo subway map. Each color in the image has an important information. But for the color blinds, similar colors cannot be distinguished. If we can convert those colors to different gray values, they can distinguish them. Therefore we try to convert color images to monochrome images.

Keywords: color-blind, JPEG, monochrome image, denoise

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2683 An Accurate Computation of 2D Zernike Moments via Fast Fourier Transform

Authors: Mohammed S. Al-Rawi, J. Bastos, J. Rodriguez

Abstract:

Object detection and object recognition are essential components of every computer vision system. Despite the high computational complexity and other problems related to numerical stability and accuracy, Zernike moments of 2D images (ZMs) have shown resilience when used in object recognition and have been used in various image analysis applications. In this work, we propose a novel method for computing ZMs via Fast Fourier Transform (FFT). Notably, this is the first algorithm that can generate ZMs up to extremely high orders accurately, e.g., it can be used to generate ZMs for orders up to 1000 or even higher. Furthermore, the proposed method is also simpler and faster than the other methods due to the availability of FFT software and/or hardware. The accuracies and numerical stability of ZMs computed via FFT have been confirmed using the orthogonality property. We also introduce normalizing ZMs with Neumann factor when the image is embedded in a larger grid, and color image reconstruction based on RGB normalization of the reconstructed images. Astonishingly, higher-order image reconstruction experiments show that the proposed methods are superior, both quantitatively and subjectively, compared to the q-recursive method.

Keywords: Chebyshev polynomial, fourier transform, fast algorithms, image recognition, pseudo Zernike moments, Zernike moments

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2682 Improvement of Cross Range Resolution in Through Wall Radar Imaging Using Bilateral Backprojection

Authors: Rashmi Yadawad, Disha Narayanan, Ravi Gautam

Abstract:

Through Wall Radar Imaging is gaining increasing importance now a days in the field of Defense and one of the most important criteria that forms the basis for the image quality obtained is the Cross-Range resolution of the image. In this research paper, the Bilateral Back projection algorithm has been implemented for Through Wall Radar Imaging. The sole purpose is to enhance the resolution in the cross range direction of the obtained Back projection image. Synthetic Data is generated for two targets which are placed at various locations in a room of dimensions 8 m by 6m. Two algorithms namely, simple back projection and Bilateral Back projection have been implemented, images are obtained and the obtained images are compared. Numerical simulations have been coded in MATLAB and experimental results of the two algorithms have been shown. Based on the comparison between the two images, it can be clearly seen that the ringing effect and chess board effect have been heavily reduced in the bilaterally back projected image and hence promising results are obtained giving a relatively sharper image with relatively well defined edges.

Keywords: through wall radar imaging, bilateral back projection, cross range resolution, synthetic data

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2681 Acute and Subacute Toxicity of the Aqueous Extract of the Bark Stems of Balanites aegyptiaca (L.) Delile in Wistar Rats

Authors: Brahim Sow

Abstract:

Background: Throughout West Africa, Balanites aegyptiaca (BA), or Zygophyllaceae, is widely used in traditional medicine to treat diabetes, hypertension, inflammation, malaria and liver disorders. In our recent research, we found that BA has nephroprotective potential against diabetes mellitus, hypertension and kidney disorders. However, to our knowledge, no systematic studies have been carried out on its derivative (toxicity) profile. Aim of the study: The study was conducted to assess the potential potency of the hydroalcoholic extract of BA bark in rats by the acute and sub-acute oral route. Materials and methods: Male and female rats in the acute depression study received BA extract orally at single doses of 500 mg/kg, 2000 mg/kg, 3000 mg/kg and 5000 mg/kg (n = 6 per group/sex). To assess acute depression, abnormal behaviour, toxic symptoms, weight and death were observed for 14 consecutive days. For the subacute impairment study, Wistar rats received the extract orally at doses of 125, 250 and 500 mg/kg (n=6 per group/sex) per day for 28 days. Behaviour and body weight were monitored daily. At the end of the treatment period, biochemical, haematological and histopathological examinations were performed, and gross and histopathological examinations of several organs were carried out. To determine the presence or absence of phytochemicals, the BA extract was subjected to gage phage chromatographic examination. Results: The absence of absorption chromatography of BA indicates the absence of cyanide groups. This suggests that the BA extract does not contain toxic substances. No mortality or adverse effects were observed at 5000 mg/kg in the acute depression test. With regard to body weight, general behaviour, relative organ weights, haematological and biochemical parameters, BA extract did not induce any mortality or potentially treatment-related effects in the sub-acute study. The normal architecture of the vital organs was revealed by histopathological examination, indicating the absence of morphological alterations. Conclusion: BA extract administered orally for 28 days at doses up to 500 mg/kg did not cause toxicological damage in rats in the present study. The median lethal dose (LD50) of the extract was estimated to be over 5000 mg/kg in an acute hyperglycaemia study.

Keywords: Balanites aegyptiaca L Delile, haematology, biochemistry, rat

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2680 Mathematical Reconstruction of an Object Image Using X-Ray Interferometric Fourier Holography Method

Authors: M. K. Balyan

Abstract:

The main principles of X-ray Fourier interferometric holography method are discussed. The object image is reconstructed by the mathematical method of Fourier transformation. The three methods are presented – method of approximation, iteration method and step by step method. As an example the complex amplitude transmission coefficient reconstruction of a beryllium wire is considered. The results reconstructed by three presented methods are compared. The best results are obtained by means of step by step method.

Keywords: dynamical diffraction, hologram, object image, X-ray holography

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2679 Saliency Detection Using a Background Probability Model

Authors: Junling Li, Fang Meng, Yichun Zhang

Abstract:

Image saliency detection has been long studied, while several challenging problems are still unsolved, such as detecting saliency inaccurately in complex scenes or suppressing salient objects in the image borders. In this paper, we propose a new saliency detection algorithm in order to solving these problems. We represent the image as a graph with superixels as nodes. By considering appearance similarity between the boundary and the background, the proposed method chooses non-saliency boundary nodes as background priors to construct the background probability model. The probability that each node belongs to the model is computed, which measures its similarity with backgrounds. Thus we can calculate saliency by the transformed probability as a metric. We compare our algorithm with ten-state-of-the-art salient detection methods on the public database. Experimental results show that our simple and effective approach can attack those challenging problems that had been baffling in image saliency detection.

Keywords: visual saliency, background probability, boundary knowledge, background priors

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2678 Endometrial Thickness Cut-Off for Evacuation of Retained Product of Conception

Authors: Nambiar Ritu, Ali Ban, Munawar Farida, Israell Imelda, T. Farouk Eman Rasheeda, Jangalgi Renuka, S. Boma Nellie

Abstract:

Aim: To define the ultrasonographic endometrial thickness (USG ET) cutoff for evacuation of retained pieces of conception (ERPC). Background: Studies of conservative management of 1st trimester miscarriage have questioned the need for post miscarriage curettage. Therapeutic decision making with transvaginal scan post miscarriage endometrial thickness in patients clinically thought to be incomplete miscarriage is often not clear. Method: Retrospective analysis of all 1ST trimester ERPC at Al Rahba Hospital from June 2012 to July 2013 was done. Total of 164 patients underwent ERPC. All cases were reviewed for pre-operative USG ET and post ERPC histopathological examination. TVS was done to evaluate the maximum ET of the uterine cavity along the long axis of the uterus and features of retained products was noted. All cases without preoperative USG ET measurement were excluded from the study, therefore only 62 out of 164 cases were included in the study. The patients were divided into three groups: o Group A: have retained products within endometrial cavity. o Group B: endometrial thickness equal or more than 20 mm. o Group C: endometrial thickness equal or less than 19.9 mm. o Post ERPC product was sent for HPE and the results were compared. Transvaginal sonographic findings can be used as a deciding factor in the management of patients with 1st trimester miscarriage who need ERPC. Our proposed cutoff in clinically stable patients requiring ERPC is more than 20 mm.

Keywords: ERPC, histopathological examination, long axis of the uterus, USG ET

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2677 The Resistance Reader Program Based on Image Processing

Authors: Janpen Srijan, Nahathai Tanmang, Thanit Purathanang, Anun Dowchern, Saksit Summart, Seangduan Kampimpa

Abstract:

This paper presents the resistance reader program based on image processing by using MATLAB. The proposed program is divided into six parts; the first part is the web camera; the second part is a watt selection before shooting the resistor; the third part is a part of finding the position of the color on the mid-point of resistor; the fourth part is a part of identifying color code of the resistor; the fifth part is a part of taking the number of values for each color for resistance calculation and the last part is a part of displaying result of resistance value. The experimental result of the resistance reader program based on image processing was able to display the resistance value of resistor. The accuracy of proposed program is 85 percent for 1 watt resistor. It has 15 percent of reading error because a problem with the color code of some resistor was too bright.

Keywords: resistance reader program, image processing, resistor, MATLAB

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2676 Retrieving Similar Segmented Objects Using Motion Descriptors

Authors: Konstantinos C. Kartsakalis, Angeliki Skoura, Vasileios Megalooikonomou

Abstract:

The fuzzy composition of objects depicted in images acquired through MR imaging or the use of bio-scanners has often been a point of controversy for field experts attempting to effectively delineate between the visualized objects. Modern approaches in medical image segmentation tend to consider fuzziness as a characteristic and inherent feature of the depicted object, instead of an undesirable trait. In this paper, a novel technique for efficient image retrieval in the context of images in which segmented objects are either crisp or fuzzily bounded is presented. Moreover, the proposed method is applied in the case of multiple, even conflicting, segmentations from field experts. Experimental results demonstrate the efficiency of the suggested method in retrieving similar objects from the aforementioned categories while taking into account the fuzzy nature of the depicted data.

Keywords: fuzzy object, fuzzy image segmentation, motion descriptors, MRI imaging, object-based image retrieval

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2675 Nation Branding: Guidelines for Identity Development and Image Perception of Thailand Brand in Health and Wellness Tourism

Authors: Jiraporn Prommaha

Abstract:

The purpose of this research is to study the development of Thailand Brand Identity and the perception of its image in order to find any guidelines for the identity development and the image perception of Thailand Brand in Health and Wellness Tourism. The paper is conducted through mixed methods research, both the qualitative and quantitative researches. The qualitative focuses on the in-depth interview of executive administrations from public and private sectors involved scholars and experts in identity and image issue, main 11 people. The quantitative research was done by the questionnaires to collect data from foreign tourists 800; Chinese tourists 400 and UK tourists 400. The technique used for this was the Exploratory Factor Analysis (EFA), this was to determine the relation between the structures of the variables by categorizing the variables into group by applying the Varimax rotation technique. This technique showed recognition the Thailand brand image related to the 2 countries, China and UK. The results found that guidelines for brand identity development and image perception of health and wellness tourism in Thailand; as following (1) Develop communication in order to understanding of the meaning of the word 'Health and beauty tourism' throughout the country, (2) Develop human resources as a national agenda, (3) Develop awareness rising in the conservation and preservation of natural resources of the country, (4) Develop the cooperation of all stakeholders in Health and Wellness Businesses, (5) Develop digital communication throughout the country and (6) Develop safety in Tourism.

Keywords: brand identity, image perception, nation branding, health and wellness tourism, mixed methods research

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2674 Histopathological and Biochemical Evaluation of Hydroxyurea-Induced Hepato-Pulmonary Toxicity and Lymphoid Necrosis in Rats

Authors: Samah Oda, Asmaa Khafaga, Mohammed Hashim, Asmaa Khamis

Abstract:

Toxicity of hydroxyurea (HU), a treatment for certain tumors, polycythemia, and thrombocytosis, was evaluated in rats in one-month toxicity study. Sixty male albino rats were equally classified into four groups. Rats received daily oral gavage of HU in 0, 250, 500, and 750 mg/kg b.wt. Chemical and histopathological assessment of liver, lung, spleen, and bone marrow was performed at 10, 20, and 30 days of the experiment. No significant change was reported in alanine aminotransferase (ALT), aspartate aminotransferase (AST), globulin, and albumin/ globulin ratio during the experiment. Significant decreases in alkaline phosphatase (ALP) and total albumin were reported in rats received 500 and 750 mg/kg b.wt of HU. In addition, total cholesterol level increased significantly after 10 days; however, it significantly decreased after 20 and 30 days of the experiment. Moreover, hepatocytic vacuolation and necrosis with portal inflammatory infiltrates were reported along experimental periods. Pulmonary congestion, hemorrhage, interstitial mononuclear infiltration, peribronchitis, and bronchial epithelial necrosis were also reported. Severe lymphocytic necrosis in spleen and severe loss of hematopoietic cells and replacement with corresponding adipose tissue in bone marrow tissues was demonstrated. In conclusion, HU could be able to induce severe dose and time-dependent hepato-pulmonary toxicity and lymphoid depression in rats.

Keywords: hydroxyurea, hepato-pulmonary toxicity, lymphoid depression, histopathology

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2673 Airborne SAR Data Analysis for Impact of Doppler Centroid on Image Quality and Registration Accuracy

Authors: Chhabi Nigam, S. Ramakrishnan

Abstract:

This paper brings out the analysis of the airborne Synthetic Aperture Radar (SAR) data to study the impact of Doppler centroid on Image quality and geocoding accuracy from the perspective of Stripmap mode of data acquisition. Although in Stripmap mode of data acquisition radar beam points at 90 degrees broad side (side looking), shift in the Doppler centroid is invariable due to platform motion. In-accurate estimation of Doppler centroid leads to poor image quality and image miss-registration. The effect of Doppler centroid is analyzed in this paper using multiple sets of data collected from airborne platform. Occurrences of ghost (ambiguous) targets and their power levels have been analyzed that impacts appropriate choice of PRF. Effect of aircraft attitudes (roll, pitch and yaw) on the Doppler centroid is also analyzed with the collected data sets. Various stages of the RDA (Range Doppler Algorithm) algorithm used for image formation in Stripmap mode, range compression, Doppler centroid estimation, azimuth compression, range cell migration correction are analyzed to find the performance limits and the dependence of the imaging geometry on the final image. The ability of Doppler centroid estimation to enhance the imaging accuracy for registration are also illustrated in this paper. The paper also tries to bring out the processing of low squint SAR data, the challenges and the performance limits imposed by the imaging geometry and the platform dynamics on the final image quality metrics. Finally, the effect on various terrain types, including land, water and bright scatters is also presented.

Keywords: ambiguous target, Doppler Centroid, image registration, Airborne SAR

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2672 Underwater Image Enhancement and Reconstruction Using CNN and the MultiUNet Model

Authors: Snehal G. Teli, R. J. Shelke

Abstract:

CNN and MultiUNet models are the framework for the proposed method for enhancing and reconstructing underwater images. Multiscale merging of features and regeneration are both performed by the MultiUNet. CNN collects relevant features. Extensive tests on benchmark datasets show that the proposed strategy performs better than the latest methods. As a result of this work, underwater images can be represented and interpreted in a number of underwater applications with greater clarity. This strategy will advance underwater exploration and marine research by enhancing real-time underwater image processing systems, underwater robotic vision, and underwater surveillance.

Keywords: convolutional neural network, image enhancement, machine learning, multiunet, underwater images

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2671 Glucose Monitoring System Using Machine Learning Algorithms

Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

Abstract:

The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

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2670 Low-Cost Image Processing System for Evaluating Pavement Surface Distress

Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

Abstract:

Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

Procedia PDF Downloads 181
2669 NANCY: Combining Adversarial Networks with Cycle-Consistency for Robust Multi-Modal Image Registration

Authors: Mirjana Ruppel, Rajendra Persad, Amit Bahl, Sanja Dogramadzi, Chris Melhuish, Lyndon Smith

Abstract:

Multimodal image registration is a profoundly complex task which is why deep learning has been used widely to address it in recent years. However, two main challenges remain: Firstly, the lack of ground truth data calls for an unsupervised learning approach, which leads to the second challenge of defining a feasible loss function that can compare two images of different modalities to judge their level of alignment. To avoid this issue altogether we implement a generative adversarial network consisting of two registration networks GAB, GBA and two discrimination networks DA, DB connected by spatial transformation layers. GAB learns to generate a deformation field which registers an image of the modality B to an image of the modality A. To do that, it uses the feedback of the discriminator DB which is learning to judge the quality of alignment of the registered image B. GBA and DA learn a mapping from modality A to modality B. Additionally, a cycle-consistency loss is implemented. For this, both registration networks are employed twice, therefore resulting in images ˆA, ˆB which were registered to ˜B, ˜A which were registered to the initial image pair A, B. Thus the resulting and initial images of the same modality can be easily compared. A dataset of liver CT and MRI was used to evaluate the quality of our approach and to compare it against learning and non-learning based registration algorithms. Our approach leads to dice scores of up to 0.80 ± 0.01 and is therefore comparable to and slightly more successful than algorithms like SimpleElastix and VoxelMorph.

Keywords: cycle consistency, deformable multimodal image registration, deep learning, GAN

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2668 Heuristic Spatial-Spectral Hyperspectral Image Segmentation Using Bands Quartile Box Plot Profiles

Authors: Mohamed A. Almoghalis, Osman M. Hegazy, Ibrahim F. Imam, Ali H. Elbastawessy

Abstract:

This paper presents a new hyperspectral image segmentation scheme with respect to both spatial and spectral contexts. The scheme uses the 8-pixels spatial pattern to build a weight structure that holds the number of outlier bands for each pixel among its neighborhood windows in different directions. The number of outlier bands for a pixel is obtained using bands quartile box plots profile among spatial 8-pixels pattern windows. The quartile box plot weight structure represents the spatial-spectral context in the image. Instead of starting segmentation process by single pixels, the proposed methodology starts by pixels groups that proved to share the same spectral features with respect to their spatial context. As a result, the segmentation scheme starts with Jigsaw pieces that build a mosaic image. The following step builds a model for each Jigsaw piece in the mosaic image. Each Jigsaw piece will be merged with another Jigsaw piece using KNN applied to their bands' quartile box plots profiles. The scheme iterates till required number of segments reached. Experiments use two data sets obtained from Earth Observer 1 (EO-1) sensor for Egypt and France. Initial results qualitative analysis showed encouraging results compared with ground truth. Quantitative analysis for the results will be included in the final paper.

Keywords: hyperspectral image segmentation, image processing, remote sensing, box plot

Procedia PDF Downloads 605
2667 Neighborhood Graph-Optimized Preserving Discriminant Analysis for Image Feature Extraction

Authors: Xiaoheng Tan, Xianfang Li, Tan Guo, Yuchuan Liu, Zhijun Yang, Hongye Li, Kai Fu, Yufang Wu, Heling Gong

Abstract:

The image data collected in reality often have high dimensions, and it contains noise and redundant information. Therefore, it is necessary to extract the compact feature expression of the original perceived image. In this process, effective use of prior knowledge such as data structure distribution and sample label is the key to enhance image feature discrimination and robustness. Based on the above considerations, this paper proposes a local preserving discriminant feature learning model based on graph optimization. The model has the following characteristics: (1) Locality preserving constraint can effectively excavate and preserve the local structural relationship between data. (2) The flexibility of graph learning can be improved by constructing a new local geometric structure graph using label information and the nearest neighbor threshold. (3) The L₂,₁ norm is used to redefine LDA, and the diagonal matrix is introduced as the scale factor of LDA, and the samples are selected, which improves the robustness of feature learning. The validity and robustness of the proposed algorithm are verified by experiments in two public image datasets.

Keywords: feature extraction, graph optimization local preserving projection, linear discriminant analysis, L₂, ₁ norm

Procedia PDF Downloads 149