Search results for: image gradients
1031 Unsupervised Segmentation Technique for Acute Leukemia Cells Using Clustering Algorithms
Authors: N. H. Harun, A. S. Abdul Nasir, M. Y. Mashor, R. Hassan
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Leukaemia is a blood cancer disease that contributes to the increment of mortality rate in Malaysia each year. There are two main categories for leukaemia, which are acute and chronic leukaemia. The production and development of acute leukaemia cells occurs rapidly and uncontrollable. Therefore, if the identification of acute leukaemia cells could be done fast and effectively, proper treatment and medicine could be delivered. Due to the requirement of prompt and accurate diagnosis of leukaemia, the current study has proposed unsupervised pixel segmentation based on clustering algorithm in order to obtain a fully segmented abnormal white blood cell (blast) in acute leukaemia image. In order to obtain the segmented blast, the current study proposed three clustering algorithms which are k-means, fuzzy c-means and moving k-means algorithms have been applied on the saturation component image. Then, median filter and seeded region growing area extraction algorithms have been applied, to smooth the region of segmented blast and to remove the large unwanted regions from the image, respectively. Comparisons among the three clustering algorithms are made in order to measure the performance of each clustering algorithm on segmenting the blast area. Based on the good sensitivity value that has been obtained, the results indicate that moving kmeans clustering algorithm has successfully produced the fully segmented blast region in acute leukaemia image. Hence, indicating that the resultant images could be helpful to haematologists for further analysis of acute leukaemia.
Keywords: Acute Leukaemia Images, Clustering Algorithms, Image Segmentation, Moving k-Means.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27711030 The Robust Clustering with Reduction Dimension
Authors: Dyah E. Herwindiati
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A clustering is process to identify a homogeneous groups of object called as cluster. Clustering is one interesting topic on data mining. A group or class behaves similarly characteristics. This paper discusses a robust clustering process for data images with two reduction dimension approaches; i.e. the two dimensional principal component analysis (2DPCA) and principal component analysis (PCA). A standard approach to overcome this problem is dimension reduction, which transforms a high-dimensional data into a lower-dimensional space with limited loss of information. One of the most common forms of dimensionality reduction is the principal components analysis (PCA). The 2DPCA is often called a variant of principal component (PCA), the image matrices were directly treated as 2D matrices; they do not need to be transformed into a vector so that the covariance matrix of image can be constructed directly using the original image matrices. The decomposed classical covariance matrix is very sensitive to outlying observations. The objective of paper is to compare the performance of robust minimizing vector variance (MVV) in the two dimensional projection PCA (2DPCA) and the PCA for clustering on an arbitrary data image when outliers are hiden in the data set. The simulation aspects of robustness and the illustration of clustering images are discussed in the end of paperKeywords: Breakdown point, Consistency, 2DPCA, PCA, Outlier, Vector Variance
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16871029 A Wavelet-Based Watermarking Method Exploiting the Contrast Sensitivity Function
Authors: John N. Ellinas, Panagiotis Kenterlis
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The efficiency of an image watermarking technique depends on the preservation of visually significant information. This is attained by embedding the watermark transparently with the maximum possible strength. The current paper presents an approach for still image digital watermarking in which the watermark embedding process employs the wavelet transform and incorporates Human Visual System (HVS) characteristics. The sensitivity of a human observer to contrast with respect to spatial frequency is described by the Contrast Sensitivity Function (CSF). The strength of the watermark within the decomposition subbands, which occupy an interval on the spatial frequencies, is adjusted according to this sensitivity. Moreover, the watermark embedding process is carried over the subband coefficients that lie on edges where distortions are less noticeable. The experimental evaluation of the proposed method shows very good results in terms of robustness and transparency.
Keywords: Image watermarking, wavelet transform, human visual system, contrast sensitivity function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20831028 FPGA based Relative Distance Measurement using Stereo Vision Technology
Authors: Manasi Pathade, Prachi Kadam, Renuka Kulkarni, Tejas Teredesai
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In this paper, we propose a novel concept of relative distance measurement using Stereo Vision Technology and discuss its implementation on a FPGA based real-time image processor. We capture two images using two CCD cameras and compare them. Disparity is calculated for each pixel using a real time dense disparity calculation algorithm. This algorithm is based on the concept of indexed histogram for matching. Disparity being inversely proportional to distance (Proved Later), we can thus get the relative distances of objects in front of the camera. The output is displayed on a TV screen in the form of a depth image (optionally using pseudo colors). This system works in real time on a full PAL frame rate (720 x 576 active pixels @ 25 fps).Keywords: Stereo Vision, Relative Distance Measurement, Indexed Histogram, Real time FPGA Image Processor
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29881027 The Control Vector Scheme for Design of Planar Primitive PH curves
Authors: Ching-Shoei Chiang, Sheng-Hsin Tsai, James Chen
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The PH curve can be constructed by given parameters, but the shape of the curve is not so easy to image from the value of the parameters. On the contract, Bézier curve can be constructed by the control polygon, and from the control polygon, we can image the figure of the curve. In this paper, we want to use the hodograph of Bézier curve to construct PH curve by selecting part of the control vectors, and produce other control vectors, so the property of PH curve exists.Keywords: PH curve, hodograph, Bézier curve.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14811026 Histogram Slicing to Better Reveal Special Thermal Objects
Authors: S. Ratna Sulistiyanti, Adhi Susanto, Thomas Sri Widodo, Gede Bayu Suparta
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In this paper, an experimentation to enhance the visibility of hot objects in a thermal image acquired with ordinary digital camera is reported, after the applications of lowpass and median filters to suppress the distracting granular noises. The common thresholding and slicing techniques were used on the histogram at different gray levels, followed by a subjective comparative evaluation. The best result came out with the threshold level 115 and the number of slices 3.Keywords: enhance, thermal image, thresholding and slicingtechniques, granular noise, hot objects.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17201025 The Use of Classifiers in Image Analysis of Oil Wells Profiling Process and the Automatic Identification of Events
Authors: Jaqueline M. R. Vieira
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Different strategies and tools are available at the oil and gas industry for detecting and analyzing tension and possible fractures in borehole walls. Most of these techniques are based on manual observation of the captured borehole images. While this strategy may be possible and convenient with small images and few data, it may become difficult and suitable to errors when big databases of images must be treated. While the patterns may differ among the image area, depending on many characteristics (drilling strategy, rock components, rock strength, etc.). In this work we propose the inclusion of data-mining classification strategies in order to create a knowledge database of the segmented curves. These classifiers allow that, after some time using and manually pointing parts of borehole images that correspond to tension regions and breakout areas, the system will indicate and suggest automatically new candidate regions, with higher accuracy. We suggest the use of different classifiers methods, in order to achieve different knowledge dataset configurations.
Keywords: Brazil, classifiers, data-mining, Image Segmentation, oil well visualization, classifiers.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25341024 Volterra Filtering Techniques for Removal of Gaussian and Mixed Gaussian-Impulse Noise
Authors: M. B. Meenavathi, K. Rajesh
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In this paper, we propose a new class of Volterra series based filters for image enhancement and restoration. Generally the linear filters reduce the noise and cause blurring at the edges. Some nonlinear filters based on median operator or rank operator deal with only impulse noise and fail to cancel the most common Gaussian distributed noise. A class of second order Volterra filters is proposed to optimize the trade-off between noise removal and edge preservation. In this paper, we consider both the Gaussian and mixed Gaussian-impulse noise to test the robustness of the filter. Image enhancement and restoration results using the proposed Volterra filter are found to be superior to those obtained with standard linear and nonlinear filters.
Keywords: Gaussian noise, Image enhancement, Imagerestoration, Linear filters, Nonlinear filters, Volterra series.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27171023 A Sub-Pixel Image Registration Technique with Applications to Defect Detection
Authors: Zhen-Hui Hu, Jyh-Shong Ju, Ming-Hwei Perng
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This paper presents a useful sub-pixel image registration method using line segments and a sub-pixel edge detector. In this approach, straight line segments are first extracted from gray images at the pixel level before applying the sub-pixel edge detector. Next, all sub-pixel line edges are mapped onto the orientation-distance parameter space to solve for line correspondence between images. Finally, the registration parameters with sub-pixel accuracy are analytically solved via two linear least-square problems. The present approach can be applied to various fields where fast registration with sub-pixel accuracy is required. To illustrate, the present approach is applied to the inspection of printed circuits on a flat panel. Numerical example shows that the present approach is effective and accurate when target images contain a sufficient number of line segments, which is true in many industrial problems.Keywords: Defect detection, Image registration, Straight line segment, Sub-pixel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19431022 X-Corner Detection for Camera Calibration Using Saddle Points
Authors: Abdulrahman S. Alturki, John S. Loomis
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This paper discusses a corner detection algorithm for camera calibration. Calibration is a necessary step in many computer vision and image processing applications. Robust corner detection for an image of a checkerboard is required to determine intrinsic and extrinsic parameters. In this paper, an algorithm for fully automatic and robust X-corner detection is presented. Checkerboard corner points are automatically found in each image without user interaction or any prior information regarding the number of rows or columns. The approach represents each X-corner with a quadratic fitting function. Using the fact that the X-corners are saddle points, the coefficients in the fitting function are used to identify each corner location. The automation of this process greatly simplifies calibration. Our method is robust against noise and different camera orientations. Experimental analysis shows the accuracy of our method using actual images acquired at different camera locations and orientations.Keywords: Camera Calibration, Corner Detector, Saddle Points, X-Corners.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31321021 Paddy/Rice Singulation for Determination of Husking Efficiency and Damage Using Machine Vision
Authors: M. Shaker, S. Minaei, M. H. Khoshtaghaza, A. Banakar, A. Jafari
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In this study a system of machine vision and singulation was developed to separate paddy from rice and determine paddy husking and rice breakage percentages. The machine vision system consists of three main components including an imaging chamber, a digital camera, a computer equipped with image processing software. The singulation device consists of a kernel holding surface, a motor with vacuum fan, and a dimmer. For separation of paddy from rice (in the image), it was necessary to set a threshold. Therefore, some images of paddy and rice were sampled and the RGB values of the images were extracted using MATLAB software. Then mean and standard deviation of the data were determined. An Image processing algorithm was developed using MATLAB to determine paddy/rice separation and rice breakage and paddy husking percentages, using blue to red ratio. Tests showed that, a threshold of 0.75 is suitable for separating paddy from rice kernels. Results from the evaluation of the image processing algorithm showed that the accuracies obtained with the algorithm were 98.36% and 91.81% for paddy husking and rice breakage percentage, respectively. Analysis also showed that a suction of 45 mmHg to 50 mmHg yielding 81.3% separation efficiency is appropriate for operation of the kernel singulation system.
Keywords: Computer vision, rice kernel, husking, breakage.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15101020 A New Method for Image Classification Based on Multi-level Neural Networks
Authors: Samy Sadek, Ayoub Al-Hamadi, Bernd Michaelis, Usama Sayed
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In this paper, we propose a supervised method for color image classification based on a multilevel sigmoidal neural network (MSNN) model. In this method, images are classified into five categories, i.e., “Car", “Building", “Mountain", “Farm" and “Coast". This classification is performed without any segmentation processes. To verify the learning capabilities of the proposed method, we compare our MSNN model with the traditional Sigmoidal Neural Network (SNN) model. Results of comparison have shown that the MSNN model performs better than the traditional SNN model in the context of training run time and classification rate. Both color moments and multi-level wavelets decomposition technique are used to extract features from images. The proposed method has been tested on a variety of real and synthetic images.Keywords: Image classification, multi-level neural networks, feature extraction, wavelets decomposition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16341019 A Neural Network Classifier for Estimation of the Degree of Infestation by Late Blight on Tomato Leaves
Authors: Gizelle K. Vianna, Gabriel V. Cunha, Gustavo S. Oliveira
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Foliage diseases in plants can cause a reduction in both quality and quantity of agricultural production. Intelligent detection of plant diseases is an essential research topic as it may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. This work investigates ways to recognize the late blight disease from the analysis of tomato digital images, collected directly from the field. A pair of multilayer perceptron neural network analyzes the digital images, using data from both RGB and HSL color models, and classifies each image pixel. One neural network is responsible for the identification of healthy regions of the tomato leaf, while the other identifies the injured regions. The outputs of both networks are combined to generate the final classification of each pixel from the image and the pixel classes are used to repaint the original tomato images by using a color representation that highlights the injuries on the plant. The new images will have only green, red or black pixels, if they came from healthy or injured portions of the leaf, or from the background of the image, respectively. The system presented an accuracy of 97% in detection and estimation of the level of damage on the tomato leaves caused by late blight.
Keywords: Artificial neural networks, digital image processing, pattern recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25371018 Tracking Objects in Color Image Sequences: Application to Football Images
Authors: Mourad Moussa, Ali Douik, Hassani Messaoud
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In this paper, we present a comparative study between two computer vision systems for objects recognition and tracking, these algorithms describe two different approach based on regions constituted by a set of pixels which parameterized objects in shot sequences. For the image segmentation and objects detection, the FCM technique is used, the overlapping between cluster's distribution is minimized by the use of suitable color space (other that the RGB one). The first technique takes into account a priori probabilities governing the computation of various clusters to track objects. A Parzen kernel method is described and allows identifying the players in each frame, we also show the importance of standard deviation value research of the Gaussian probability density function. Region matching is carried out by an algorithm that operates on the Mahalanobis distance between region descriptors in two subsequent frames and uses singular value decomposition to compute a set of correspondences satisfying both the principle of proximity and the principle of exclusion.
Keywords: Image segmentation, objects tracking, Parzen window, singular value decomposition, target recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19641017 Segmentation of Gray Scale Images of Dropwise Condensation on Textured Surfaces
Authors: Helene Martin, Solmaz Boroomandi Barati, Jean-Charles Pinoli, Stephane Valette, Yann Gavet
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In the present work we developed an image processing algorithm to measure water droplets characteristics during dropwise condensation on pillared surfaces. The main problem in this process is the similarity between shape and size of water droplets and the pillars. The developed method divides droplets into four main groups based on their size and applies the corresponding algorithm to segment each group. These algorithms generate binary images of droplets based on both their geometrical and intensity properties. The information related to droplets evolution during time including mean radius and drops number per unit area are then extracted from the binary images. The developed image processing algorithm is verified using manual detection and applied to two different sets of images corresponding to two kinds of pillared surfaces.Keywords: Dropwise condensation, textured surface, image processing, watershed.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6761016 Image Processing on Geosynthetic Reinforced Layers to Evaluate Shear Strength and Variations of the Strain Profiles
Authors: S. K. Khosrowshahi, E. Güler
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This study investigates the reinforcement function of geosynthetics on the shear strength and strain profile of sand. Conducting a series of simple shear tests, the shearing behavior of the samples under static and cyclic loads was evaluated. Three different types of geosynthetics including geotextile and geonets were used as the reinforcement materials. An image processing analysis based on the optical flow method was performed to measure the lateral displacements and estimate the shear strains. It is shown that besides improving the shear strength, the geosynthetic reinforcement leads a remarkable reduction on the shear strains. The improved layer reduces the required thickness of the soil layer to resist against shear stresses. Consequently, the geosynthetic reinforcement can be considered as a proper approach for the sustainable designs, especially in the projects with huge amount of geotechnical applications like subgrade of the pavements, roadways, and railways.Keywords: Image processing, soil reinforcement, geosynthetics, simple shear test, shear strain profile.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10301015 Sediment Wave and Cyclic Steps as Mechanism for Sediment Transport in Submarine Canyons Thalweg
Authors: Taiwo Olusoji Lawrence, Peace Mawo Aaron
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Seismic analysis of bedforms has proven to be one of the best ways to study deepwater sedimentary features. Canyons are known to be sediment transportation conduit. Sediment wave are large-scale depositional bedforms in various parts of the world's oceans formed predominantly by suspended load transport. These undulating objects usually have tens of meters to a few kilometers in wavelength and a height of several meters. Cyclic steps have long long-wave upstream-migrating bedforms confined by internal hydraulic jumps. They usually occur in regions with high gradients and slope breaks. Cyclic steps and migrating sediment waves are the most common bedform on the seafloor. Cyclic steps and related sediment wave bedforms are significant to the morpho-dynamic evolution of deep-water depositional systems architectural elements, especially those located along tectonically active margins with high gradients and slope breaks that can promote internal hydraulic jumps in turbidity currents. This report examined sedimentary activities and sediment transportation in submarine canyons and provided distinctive insight into factors that created a complex seabed canyon system in the Ceara Fortaleza basin Brazilian Equatorial Margin (BEM). The growing importance of cyclic steps made it imperative to understand the parameters leading to their formation, migration, and architecture as well as their controls on sediment transport in canyon thalweg. We extracted the parameters of the observed bedforms and evaluated the aspect ratio and asymmetricity. We developed a relationship between the hydraulic jump magnitude, depth of the hydraulic fall and the length of the cyclic step therein. It was understood that an increase in the height of the cyclic step increases the magnitude of the hydraulic jump and thereby increases the rate of deposition on the preceding stoss side. An increase in the length of the cyclic steps reduces the magnitude of the hydraulic jump and reduces the rate of deposition at the stoss side. Therefore, flat stoss side was noticed at most preceding cyclic step and sediment wave.Keywords: Ceara Fortaleza, sediment wave, cyclic steps, submarine canyons.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7931014 A Context-Sensitive Algorithm for Media Similarity Search
Authors: Guang-Ho Cha
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This paper presents a context-sensitive media similarity search algorithm. One of the central problems regarding media search is the semantic gap between the low-level features computed automatically from media data and the human interpretation of them. This is because the notion of similarity is usually based on high-level abstraction but the low-level features do not sometimes reflect the human perception. Many media search algorithms have used the Minkowski metric to measure similarity between image pairs. However those functions cannot adequately capture the aspects of the characteristics of the human visual system as well as the nonlinear relationships in contextual information given by images in a collection. Our search algorithm tackles this problem by employing a similarity measure and a ranking strategy that reflect the nonlinearity of human perception and contextual information in a dataset. Similarity search in an image database based on this contextual information shows encouraging experimental results.
Keywords: Context-sensitive search, image search, media search, similarity ranking, similarity search.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6231013 Development of a Mobile Image-Based Reminder Application to Support Tuberculosis Treatment in Africa
Authors: Haji Ali Haji, Hussein Suleman, Ulrike Rivett
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This paper presents the design, development and evaluation of an application prototype developed to support tuberculosis (TB) patients’ treatment adherence. The system makes use of graphics and voice reminders as opposed to text messaging to encourage patients to follow their medication routine. To evaluate the effect of the prototype applications, participants were given mobile phones on which the reminder system was installed. Thirty-eight people, including TB health workers and patients from Zanzibar, Tanzania, participated in the evaluation exercises. The results indicate that the participants found the mobile image-based application is useful to support TB treatment. All participants understood and interpreted the intended meaning of every image correctly. The study findings revealed that the use of a mobile visualbased application may have potential benefit to support TB patients (both literate and illiterate) in their treatment processes.Keywords: ICT4D, mobile technology, tuberculosis, visualbased reminder.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19541012 Bernstein-Galerkin Approach for Perturbed Constant-Coefficient Differential Equations, One-Dimensional Analysis
Authors: Diego Garijo
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A numerical approach for solving constant-coefficient differential equations whose solutions exhibit boundary layer structure is built by inserting Bernstein Partition of Unity into Galerkin variational weak form. Due to the reproduction capability of Bernstein basis, such implementation shows excellent accuracy at boundaries and is able to capture sharp gradients of the field variable by p-refinement using regular distributions of equi-spaced evaluation points. The approximation is subjected to convergence experimentation and a procedure to assemble the discrete equations without a background integration mesh is proposed.
Keywords: Bernstein polynomials, Galerkin, differential equation, boundary layer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18291011 Detecting and Measuring Fabric Pills Using Digital Image Analysis
Authors: Dariush Semnani, Hossein Ghayoor
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In this paper a novel method was presented for evaluating the fabric pills using digital image processing techniques. This work provides a novel technique for detecting pills and also measuring their heights, surfaces and volumes. Surely, measuring the intensity of defects by human vision is an inaccurate method for quality control; as a result, this problem became a motivation for employing digital image processing techniques for detection of defects of fabric surface. In the former works, the systems were just limited to measuring of the surface of defects, but in the presented method the height and the volume of defects were also measured, which leads to a more accurate quality control. An algorithm was developed to first, find pills and then measure their average intensity by using three criteria of height, surface and volume. The results showed a meaningful relation between the number of rotations and the quality of pilled fabrics.Keywords: 3D analysis, computer vision, fabric, pile, surface evaluation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26081010 Integration of Image and Patient Data, Software and International Coding Systems for Use in a Mammography Research Project
Authors: V. Balanica, W. I. D. Rae, M. Caramihai, S. Acho, C. P. Herbst
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Mammographic images and data analysis to facilitate modelling or computer aided diagnostic (CAD) software development should best be done using a common database that can handle various mammographic image file formats and relate these to other patient information. This would optimize the use of the data as both primary reporting and enhanced information extraction of research data could be performed from the single dataset. One desired improvement is the integration of DICOM file header information into the database, as an efficient and reliable source of supplementary patient information intrinsically available in the images. The purpose of this paper was to design a suitable database to link and integrate different types of image files and gather common information that can be further used for research purposes. An interface was developed for accessing, adding, updating, modifying and extracting data from the common database, enhancing the future possible application of the data in CAD processing. Technically, future developments envisaged include the creation of an advanced search function to selects image files based on descriptor combinations. Results can be further used for specific CAD processing and other research. Design of a user friendly configuration utility for importing of the required fields from the DICOM files must be done.Keywords: Database Integration, Mammogram Classification, Tumour Classification, Computer Aided Diagnosis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19321009 New Efficient Method for Coding Color Images
Authors: Walaa M.Abd-Elhafiez, Wajeb Gharibi
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In this paper a novel color image compression technique for efficient storage and delivery of data is proposed. The proposed compression technique started by RGB to YCbCr color transformation process. Secondly, the canny edge detection method is used to classify the blocks into the edge and non-edge blocks. Each color component Y, Cb, and Cr compressed by discrete cosine transform (DCT) process, quantizing and coding step by step using adaptive arithmetic coding. Our technique is concerned with the compression ratio, bits per pixel and peak signal to noise ratio, and produce better results than JPEG and more recent published schemes (like CBDCT-CABS and MHC). The provided experimental results illustrate the proposed technique that is efficient and feasible in terms of compression ratio, bits per pixel and peak signal to noise ratio.
Keywords: Image compression, color image, Q-coder, quantization, edge-detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16631008 Annotations of Gene Pathways Images in Biomedical Publications Using Siamese Network
Authors: Micheal Olaolu Arowolo, Muhammad Azam, Fei He, Mihail Popescu, Dong Xu
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As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Manually annotating pathway diagrams is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy.
Keywords: Biological pathway, gene identification, object detection, Siamese network, ResNet.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2221007 The Effect of Closed Circuit Television Image Patch Layout on Performance of a Simulated Train-Platform Departure Task
Authors: Aaron J. Small, Craig A. Fletcher
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This study investigates the effect of closed circuit television (CCTV) image patch layout on performance of a simulated train-platform departure task. The within-subjects experimental design measures target detection rate and response latency during a CCTV visual search task conducted as part of the procedure for safe train dispatch. Three interface designs were developed by manipulating CCTV image patch layout. Eye movements, perceived workload and system usability were measured across experimental conditions. Task performance was compared to identify significant differences between conditions. The results of this study have not been determined.Keywords: Rail human factors, workload, closed circuit television, platform departure, attention, information processing, interface design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7181006 Estimation of Attenuation and Phase Delay in Driving Voltage Waveform of an Ultra-High-Speed Image Sensor by Dimensional Analysis
Authors: V. T. S. Dao, T. G. Etoh, C. Vo Le, H. D. Nguyen, K. Takehara, T. Akino, K. Nishi
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We present an explicit expression to estimate driving voltage attenuation through RC networks representation of an ultrahigh- speed image sensor. Elmore delay metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE simulation data, we found a simple expression that significantly improves the accuracy of the approximation. Estimation error of the resultant expression for uniform RC networks is less than 2%. Similarly, another simple closed-form model to estimate 50 % delay through fundamental RC networks is also derived with sufficient accuracy. The framework of this analysis can be extended to address delay or attenuation issues of other VLSI structures.
Keywords: Dimensional Analysis, Elmore model, RC network, Signal Attenuation, Ultra-High-Speed Image Sensor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14151005 Real-Time Image Encryption Using a 3D Discrete Dual Chaotic Cipher
Authors: M. F. Haroun, T. A. Gulliver
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In this paper, an encryption algorithm is proposed for real-time image encryption. The scheme employs a dual chaotic generator based on a three dimensional (3D) discrete Lorenz attractor. Encryption is achieved using non-autonomous modulation where the data is injected into the dynamics of the master chaotic generator. The second generator is used to permute the dynamics of the master generator using the same approach. Since the data stream can be regarded as a random source, the resulting permutations of the generator dynamics greatly increase the security of the transmitted signal. In addition, a technique is proposed to mitigate the error propagation due to the finite precision arithmetic of digital hardware. In particular, truncation and rounding errors are eliminated by employing an integer representation of the data which can easily be implemented. The simple hardware architecture of the algorithm makes it suitable for secure real-time applications.Keywords: Chaotic systems, image encryption, 3D Lorenz attractor, non-autonomous modulation, FPGA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12041004 ROI Based Embedded Watermarking of Medical Images for Secured Communication in Telemedicine
Authors: Baisa L. Gunjal, Suresh N. Mali
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Medical images require special safety and confidentiality because critical judgment is done on the information provided by medical images. Transmission of medical image via internet or mobile phones demands strong security and copyright protection in telemedicine applications. Here, highly secured and robust watermarking technique is proposed for transmission of image data via internet and mobile phones. The Region of Interest (ROI) and Non Region of Interest (RONI) of medical image are separated. Only RONI is used for watermark embedding. This technique results in exact recovery of watermark with standard medical database images of size 512x512, giving 'correlation factor' equals to 1. The correlation factor for different attacks like noise addition, filtering, rotation and compression ranges from 0.90 to 0.95. The PSNR with weighting factor 0.02 is up to 48.53 dBs. The presented scheme is non blind and embeds hospital logo of 64x64 size.
Keywords: Compression, DWT, ROI, Scrambling, Vertices
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32611003 A Novel Multiresolution based Optimization Scheme for Robust Affine Parameter Estimation
Authors: J.Dinesh Peter
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This paper describes a new method for affine parameter estimation between image sequences. Usually, the parameter estimation techniques can be done by least squares in a quadratic way. However, this technique can be sensitive to the presence of outliers. Therefore, parameter estimation techniques for various image processing applications are robust enough to withstand the influence of outliers. Progressively, some robust estimation functions demanding non-quadratic and perhaps non-convex potentials adopted from statistics literature have been used for solving these. Addressing the optimization of the error function in a factual framework for finding a global optimal solution, the minimization can begin with the convex estimator at the coarser level and gradually introduce nonconvexity i.e., from soft to hard redescending non-convex estimators when the iteration reaches finer level of multiresolution pyramid. Comparison has been made to find the performance of the results of proposed method with the results found individually using two different estimators.Keywords: Image Processing, Affine parameter estimation, Outliers, Robust Statistics, Robust M-estimators
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14451002 Empirical Survey of the Solar System Based on the Fusion of GPS and Image Processing
Authors: S. Divya Gnanarathinam, S. Sundaramurthy
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The tremendous increase in the population of the world creates the immediate need for the energy resources. All the people in the world need the sustainable energy resources which have low costs. Solar energy is appraised as one of the main energy resources in warm countries. The areas in the west of India like Rajasthan, Gujarat, etc. are immensely rich in solar energy resources. This paper deals with the development of dual axis solar tracker using Arduino board. Depending on the astronomical estimates of the sun from the GPS and sensor image processing outcomes, a methodology is proposed to locate the position of the sun to obtain the maximum solar energy. Based on the outcomes, the solar tracking system figures out whether to use image processing outcomes or astronomical estimates to attain the maximum efficiency of the solar panel. Finally, the experimental values obtained from the solar tracker for both the sunny and the rainy days are being tabulated.
Keywords: Dual axis solar tracker, Arduino board, LDR sensors, global positioning system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1575