Search results for: images processing

Authors: Somi Nah

Abstract:

The genre of fantasy depicts a world of imagine that triggers popular interest from a created view of world, and a fantasy is defined as a story that illustrates a world of imagine where scientific or horror elements are stand in its center. This study is not focused on the narrative of the fantasy, i.e. not on the adventurous story, but is concentrated on the image of the fantasy to work on its relationship with intended themes and differences among cultures due to meanings of materials. As for films, we have selected some films in the 2000's that are internationally recognized as expressing unique images of fantasy containing the theme of love in them. The selected films are 5 pieces including two European films, Amelie from Montmartre (2001) and The Science of Sleep (2005) and three Asian films, Citizen Dog from Thailand (2004), Memories of Matsuko from Japan (2006), and I'm a Cyborg, but That's OK from Korea (2006). These films share some common characteristics to the effect that they give tiny lessons and feelings for life with expressions of fantasy images as if they were fairy tales for adults and that they lead the audience to reflect on their days and revive forgotten dreams of childhood. We analyze the images of fantasy in each of the films on the basis of the elements of Mise-en-Scène (setting and props, costume, hair and make-up, facial expressions and body language, lighting and color, positioning of characters, and objects within a frame).

Keywords: Mise-en-scène, fantasy images, films, visualization.

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Authors: Ms. Yi Mon Thant

Abstract:

Animation is simply defined as the sequencing of a series of static images to generate the illusion of movement. Most people believe that actual drawings or creation of the individual images is the animation, when in actuality it is the arrangement of those static images that conveys the motion. To become an animator, it is often assumed that needed the ability to quickly design masterpiece after masterpiece. Although some semblance of artistic skill is a necessity for the job, the real key to becoming a great animator is in the comprehension of timing. This paper will use a combination of sprite animation, frame animation, and some other techniques to cause a group of multi-colored static images to slither around in the bounded area. In addition to slithering, the images will also change the color of different parts of their body, much like the real world creatures that have this amazing ability to change the colors on their bodies do. This paper was implemented by using Java 2 Standard Edition (J2SE). It is both time-consuming and expensive to create animations, regardless if they are created by hand or by using motion-capture equipment. If the animators could reuse old animations and even blend different animations together, a lot of work would be saved in the process. The main objective of this paper is to examine a method for blending several animations together in real time. This paper presents and analyses a solution using Weighted Skeleton Animation (WSA) resulting in limited CPU time and memory waste as well as saving time for the animators. The idea presented is described in detail and implemented. In this paper, text animation, vertex animation, sprite part animation and whole sprite animation were tested. In this research paper, the resolution, smoothness and movement of animated images will be carried out from the parameters, which will be obtained from the experimental research of implementing this paper.

Keywords: Weighted Skeleton Animation

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Authors: Tadatsugu Kitamoto

Abstract:

Recently, a quality of motors is inspected by human ears. In this paper, I propose two systems using a method of speech recognition for automation of the inspection. The first system is based on a method of linear processing which uses K-means and Nearest Neighbor method, and the second is based on a method of non-linear processing which uses neural networks. I used motor sounds in these systems, and I successfully recognize 86.67% of motor sounds in the linear processing system and 97.78% in the non-linear processing system.

Keywords: Acoustical diagnosis, Neural networks, K-means, Short-time Fourier transformation

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Authors: Lalita Gupta, R. P. Singh

Abstract:

Array signal processing involves signal enumeration and source localization. Array signal processing is centered on the ability to fuse temporal and spatial information captured via sampling signals emitted from a number of sources at the sensors of an array in order to carry out a specific estimation task: source characteristics (mainly localization of the sources) and/or array characteristics (mainly array geometry) estimation. Array signal processing is a part of signal processing that uses sensors organized in patterns or arrays, to detect signals and to determine information about them. Beamforming is a general signal processing technique used to control the directionality of the reception or transmission of a signal. Using Beamforming we can direct the majority of signal energy we receive from a group of array. Multiple signal classification (MUSIC) is a highly popular eigenstructure-based estimation method of direction of arrival (DOA) with high resolution. This Paper enumerates the effect of missing sensors in DOA estimation. The accuracy of the MUSIC-based DOA estimation is degraded significantly both by the effects of the missing sensors among the receiving array elements and the unequal channel gain and phase errors of the receiver.

Keywords: Array Signal Processing, Beamforming, ULA, Direction of Arrival, MUSIC

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Authors: Ahmed Zaafouri, Mounir Sayadi, Farhat Fnaiech

Abstract:

In this paper, we present a method for edge segmentation of satellite images based on 2-D Phase Congruency (PC) model. The proposed approach is composed by two steps: The contextual non linear smoothing algorithm (CNLS) is used to smooth the input images. Then, the 2D stretched Gabor filter (S-G filter) based on proposed angular variation is developed in order to avoid the multiple responses in the previous work. An assessment of our proposed method performance is provided in terms of accuracy of satellite image edge segmentation. The proposed method is compared with others known approaches.

Keywords: Edge segmentation, Phase congruency model, Satellite images, Stretched Gabor filter

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Authors: R. Rama Kishore, Sunesh

Abstract:

This paper presents an optimized, robust, and secured watermarking technique. The methodology used in this work is the combination of entropy and chaotic grid map. The proposed methodology incorporates Discrete Cosine Transform (DCT) on the host image. To improve the imperceptibility of the method, the host image DCT blocks, where the watermark is to be embedded, are further optimized by considering the entropy of the blocks. Chaotic grid is used as a key to reorder the DCT blocks so that it will further increase security while selecting the watermark embedding locations and its sequence. Without a key, one cannot reveal the exact watermark from the watermarked image. The proposed method is implemented on four different images. It is concluded that the proposed method is giving better results in terms of imperceptibility measured through PSNR and found to be above 50. In order to prove the effectiveness of the method, the performance analysis is done after implementing different attacks on the watermarked images. It is found that the methodology is very strong against JPEG compression attack even with the quality parameter up to 15. The experimental results are confirming that the combination of entropy and chaotic grid map method is strong and secured to different image processing attacks.

Keywords: Digital watermarking, discrete cosine transform, chaotic grid map, entropy.

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Authors: Nedeljko Cvejic, Artur Łoza, David Bull, Nishan Canagarajah

Abstract:

In this paper, we present a novel objective nonreference performance assessment algorithm for image fusion. It takes into account local measurements to estimate how well the important information in the source images is represented by the fused image. The metric is based on the Universal Image Quality Index and uses the similarity between blocks of pixels in the input images and the fused image as the weighting factors for the metrics. Experimental results confirm that the values of the proposed metrics correlate well with the subjective quality of the fused images, giving a significant improvement over standard measures based on mean squared error and mutual information.

Keywords: Fusion performance measures, image fusion, non-reference quality measures, objective quality measures.

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Authors: Ali Soleymani, Zulkarnain Md Ali, Md Jan Nordin

Abstract:

This paper is a review on the aspects and approaches of design an image cryptosystem. First a general introduction given for cryptography and images encryption and followed by different techniques in image encryption and related works for each technique surveyed. Finally, general security analysis methods for encrypted images are mentioned.

Keywords: Image, cryptography, encryption, security, analysis.

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Authors: Mohamad Muqtada Ali Khan, Nor Ashikin Shaari, Donny Adriansyah Bin Nazaruddin, Hafzan Eva Bt Mansoor

Abstract:

Floods play a key role in landform evolution of an area. This process is likely to alter the topography of the earth’s surface. The present study area, Kota Bharu is very prone to floods extends from upstream of Kelantan River near Kemubu to the downstream area near Kuala Besar. These flood events which occur every year in the study area exhibit a strong bearing on river morphological set-up. In the present study, three satellite imageries of different time periods have been used to manifest the post-flood landform changes. The pre-processing of the images such as subset, geometric corrections and atmospheric corrections were carried-out using ENVI 4.5 followed by the analysis processes. Twenty sets of cross sections were plotted using software Erdas 9.2, ERDAS and ArcGis 10 for the all three images. The results show a significant change in the length of the cross section which suggest that the geomorphological processes play a key role in carving and shaping the river banks during the floods. 

Keywords: Flood Induced, Geomorphic imprints, Kelantan river, Malaysia.

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Authors: H. Dujmic, V. Papic, H. Turic

Abstract:

The article presents a new method for detection of artificial objects and materials from images of the environmental (non-urban) terrain. Our approach uses the hue and saturation (or Cb and Cr) components of the image as the input to the segmentation module that uses the mean shift method. The clusters obtained as the output of this stage have been processed by the decision-making module in order to find the regions of the image with the significant possibility of representing human. Although this method will detect various non-natural objects, it is primarily intended and optimized for detection of humans; i.e. for search and rescue purposes in non-urban terrain where, in normal circumstances, non-natural objects shouldn-t be present. Real world images are used for the evaluation of the method.

Keywords: Landscape surveillance, mean shift algorithm, image segmentation, target detection.

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Authors: I. R. Farah, I. B. Ismail, M. B. Ahmed

Abstract:

The huge development of new technologies and the apparition of open communication system more and more sophisticated create a new challenge to protect digital content from piracy. Digital watermarking is a recent research axis and a new technique suggested as a solution to these problems. This technique consists in inserting identification information (watermark) into digital data (audio, video, image, databases...) in an invisible and indelible manner and in such a way not to degrade original medium-s quality. Moreover, we must be able to correctly extract the watermark despite the deterioration of the watermarked medium (i.e attacks). In this paper we propose a system for watermarking satellite images. We chose to embed the watermark into frequency domain, precisely the discrete wavelet transform (DWT). We applied our algorithm on satellite images of Tunisian center. The experiments show satisfying results. In addition, our algorithm showed an important resistance facing different attacks, notably the compression (JEPG, JPEG2000), the filtering, the histogram-s manipulation and geometric distortions such as rotation, cropping, scaling.

Keywords: Digital data watermarking, Spatial Database, Satellite images, Discrete Wavelets Transform (DWT).

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Authors: C. Yaiprasert, K. Jaroensutasinee, M. Jaroensutasinee

Abstract:

To develop a process of extracting pixel values over the using of satellite remote sensing image data in Thailand. It is a very important and effective method of forecasting rainfall. This paper presents an approach for forecasting a possible rainfall area based on pixel values from remote sensing satellite images. First, a method uses an automatic extraction process of the pixel value data from the satellite image sequence. Then, a data process is designed to enable the inference of correlations between pixel value and possible rainfall occurrences. The result, when we have a high averaged pixel value of daily water vapor data, we will also have a high amount of daily rainfall. This suggests that the amount of averaged pixel values can be used as an indicator of raining events. There are some positive associations between pixel values of daily water vapor images and the amount of daily rainfall at each rain-gauge station throughout Thailand. The proposed approach was proven to be a helpful manual for rainfall forecasting from meteorologists by which using automated analyzing and interpreting process of meteorological remote sensing data.

Keywords: Pixel values, satellite image, water vapor, rainfall, image processing.

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Authors: Y. Boutiche, N. Ramou, M. Ben Gharsallah

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This paper is devoted to present and discuss a model that allows a local segmentation by using statistical information of a given image. It is based on Chan-Vese model, curve evolution, partial differential equations and binary level sets method. The proposed model uses the piecewise constant approximation of Chan-Vese model to compute Signed Pressure Force (SPF) function, this one attracts the curve to the true object(s)-s boundaries. The implemented model is used to extract weld defects from weld radiographic images in the aim to calculate the perimeter and surfaces of those weld defects; encouraged resultants are obtained on synthetic and real radiographic images.

Keywords: Active contour, Chan-Vese Model, local segmentation, weld radiographic images.

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Authors: N. Shanmugapriya, R. Nallusamy

Abstract:

Content-based image retrieval (CBIR) uses the contents of images to characterize and contact the images. This paper focus on retrieving the image by separating images into its three color mechanism R, G and B and for that Discrete Wavelet Transformation is applied. Then Wavelet based Generalized Gaussian Density (GGD) is practical which is used for modeling the coefficients from the wavelet transforms. After that it is agreed to Histogram of Oriented Gradient (HOG) for extracting its characteristic vectors with Relevant Feedback technique is used. The performance of this approach is calculated by exactness and it confirms that this method is wellorganized for image retrieval.

Keywords: Content-Based Image Retrieval (CBIR), Relevant Feedback, Histogram of Oriented Gradient (HOG), Generalized Gaussian Density (GGD).

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Authors: H. Benjamin Fredrick David, R. Balasubramanian, A. Anbarasa Pandian

Abstract:

Image retrieval is the most interesting technique which is being used today in our digital world. CBIR, commonly expanded as Content Based Image Retrieval is an image processing technique which identifies the relevant images and retrieves them based on the patterns that are extracted from the digital images. In this paper, two research works have been presented using CBIR. The first work provides an automated and interactive approach to the analysis of CBIR techniques. CBIR works on the principle of supervised machine learning which involves feature selection followed by training and testing phase applied on a classifier in order to perform prediction. By using feature extraction, the image transforms such as Contourlet, Ridgelet and Shearlet could be utilized to retrieve the texture features from the images. The features extracted are used to train and build a classifier using the classification algorithms such as Naïve Bayes, K-Nearest Neighbour and Multi-class Support Vector Machine. Further the testing phase involves prediction which predicts the new input image using the trained classifier and label them from one of the four classes namely 1- Normal brain, 2- Benign tumour, 3- Malignant tumour and 4- Severe tumour. The second research work includes developing a tool which is used for tumour stage identification using the best feature extraction and classifier identified from the first work. Finally, the tool will be used to predict tumour stage and provide suggestions based on the stage of tumour identified by the system. This paper presents these two approaches which is a contribution to the medical field for giving better retrieval performance and for tumour stages identification.

Keywords: Brain tumour detection, content based image retrieval, classification of tumours, image retrieval.

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Authors: YasirSalih, AamirSaeed Malik, Wazirahbt.Md-Esa

Abstract:

In the recent years, high dynamic range imaging has gain popularity with the advancement in digital photography. In this contribution we present a subjective evaluation of various tone production and tone mapping techniques by a number of participants. Firstly, standard HDR images were used and the participants were asked to rate them based on a given rating scheme. After that, the participant was asked to rate HDR image generated using linear and nonlinear combination approach of multiple exposure images. The experimental results showed that linearly generated HDR images have better visualization than the nonlinear combined ones. In addition, Reinhard et al. and the exponential tone mapping operators have shown better results compared to logarithmic and the Garrett et al. tone mapping operators.

Keywords: tone mapping, high dynamic range, low dynamic range, bits per pixel.

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Authors: Nedeljko Cvejic, Artur Łoza, David Bull, Nishan Canagarajah

Abstract:

In this paper, we present a novel objective nonreference performance assessment algorithm for image fusion. It takes into account local measurements to estimate how well the important information in the source images is represented by the fused image. The metric is based on the Universal Image Quality Index and uses the similarity between blocks of pixels in the input images and the fused image as the weighting factors for the metrics. Experimental results confirm that the values of the proposed metrics correlate well with the subjective quality of the fused images, giving a significant improvement over standard measures based on mean squared error and mutual information.

Keywords: Fusion performance measures, image fusion, nonreferencequality measures, objective quality measures.

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Authors: Syed Musharaf Ali, Muhammad Younus Javed, Naveed Sarfraz Khattak, Athar Mohsin, UmarFarooq

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This paper introduces the effective speckle reduction of synthetic aperture radar (SAR) images using inner product spaces in undecimated wavelet domain. There are two major areas in projection onto span algorithm where improvement can be made. First is the use of undecimated wavelet transformation instead of discrete wavelet transformation. And second area is the use of smoothing filter namely directional smoothing filter which is an additional step. Proposed method does not need any noise estimation and thresholding technique. More over proposed method gives good results on both single polarimetric and fully polarimetric SAR images.

Keywords: Directional Smoothing, Inner product, Length ofvector, Undecimated wavelet transformation.

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Authors: Miloš Marjanović, Jaroslav Burian, Ja kub Miřijovský, Jan Harbula

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This paper regards the phenomena of intensive suburbanization and urbanization in Olomouc city and in Olomouc region in general for the period of 1986–2009. A Remote Sensing approach that involves tracking of changes in Land Cover units is proposed to quantify the urbanization state and trends in temporal and spatial aspects. It actually consisted of two approaches, Experiment 1 and Experiment 2 which implied two different image classification solutions in order to provide Land Cover maps for each 1986–2009 time split available in the Landsat image set. Experiment 1 dealt with the unsupervised classification, while Experiment 2 involved semi- supervised classification, using a combination of object-based and pixel-based classifiers. The resulting Land Cover maps were subsequently quantified for the proportion of urban area unit and its trend through time, and also for the urban area unit stability, yielding the relation of spatial and temporal development of the urban area unit. Some outcomes seem promising but there is indisputably room for improvements of source data and also processing and filtering.

Keywords: Change detection, image classification, land cover, Landsat images, Olomouc city, urbanization.

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Authors: Bhumika Gupta, Jeayaram Subramanian, Hardik Vachhrajani, Avinash Shivdas

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Indian food processing industry is one of the largest in the world in terms of production, consumption, exports and growth opportunities. SMEs play a crucial role within this. Large manufacturing firms largely dominate innovation studies in India. Innovation sources used by SMEs are often different from that of large firms. This paper focuses on exploring various sources of innovation adopted by food processing SMEs in Kerala, South India. Outcome suggests that SMEs use various sources like suppliers, competitors, employees, government/research institutions and customers to get new ideas.

Keywords: Food processing, innovation, SMEs, sources of innovation.

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Authors: FH. Sarieddeen, R. El Berbari, S. Imad, J. Abdel Baki, M. Hamad, R. Blanc, A. Nakib, Y.Chenoune

Abstract:

Brain ArterioVenous Malformation (BAVM) is an abnormal tangle of brain blood vessels where arteries shunt directly into veins with no intervening capillary bed which causes high pressure and hemorrhage risk. The success of treatment by embolization in interventional neuroradiology is highly dependent on the accuracy of the vessels visualization. In this paper the performance of clustering techniques on vessel segmentation from 3- D rotational angiography (3DRA) images is investigated and a new technique of segmentation is proposed. This method consists in: preprocessing step of image enhancement, then K-Means (KM), Fuzzy C-Means (FCM) and Expectation Maximization (EM) clustering are used to separate vessel pixels from background and artery pixels from vein pixels when possible. A post processing step of removing false-alarm components is applied before constructing a three-dimensional volume of the vessels. The proposed method was tested on six datasets along with a medical assessment of an expert. Obtained results showed encouraging segmentations.

Keywords: Brain arteriovenous malformation (BAVM), 3-D rotational angiography (3DRA), K-Means (KM) clustering, Fuzzy CMeans (FCM) clustering, Expectation Maximization (EM) clustering, volume rendering.

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Authors: P.S. Hiremath, Prema T. Akkasaligar, Sharan Badiger

Abstract:

Speckle noise affects all coherent imaging systems including medical ultrasound. In medical images, noise suppression is a particularly delicate and difficult task. A tradeoff between noise reduction and the preservation of actual image features has to be made in a way that enhances the diagnostically relevant image content. Even though wavelets have been extensively used for denoising speckle images, we have found that denoising using contourlets gives much better performance in terms of SNR, PSNR, MSE, variance and correlation coefficient. The objective of the paper is to determine the number of levels of Laplacian pyramidal decomposition, the number of directional decompositions to perform on each pyramidal level and thresholding schemes which yields optimal despeckling of medical ultrasound images, in particular. The proposed method consists of the log transformed original ultrasound image being subjected to contourlet transform, to obtain contourlet coefficients. The transformed image is denoised by applying thresholding techniques on individual band pass sub bands using a Bayes shrinkage rule. We quantify the achieved performance improvement.

Keywords: Contourlet transform, Despeckling, Pyramidal directionalfilter bank, Thresholding.

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Authors: Roshan Dharshana Yapa, Koichi Harada

Abstract:

Breast skin-line estimation and breast segmentation is an important pre-process in mammogram image processing and computer-aided diagnosis of breast cancer. Limiting the area to be processed into a specific target region in an image would increase the accuracy and efficiency of processing algorithms. In this paper we are presenting a new algorithm for estimating skin-line and breast segmentation using fast marching algorithm. Fast marching is a partial-differential equation based numerical technique to track evolution of interfaces. We have introduced some modifications to the traditional fast marching method, specifically to improve the accuracy of skin-line estimation and breast tissue segmentation. Proposed modifications ensure that the evolving front stops near the desired boundary. We have evaluated the performance of the algorithm by using 100 mammogram images taken from mini-MIAS database. The results obtained from the experimental evaluation indicate that this algorithm explains 98.6% of the ground truth breast region and accuracy of the segmentation is 99.1%. Also this algorithm is capable of partially-extracting nipple when it is available in the profile.

Keywords: Mammogram, fast marching method, mathematical morphology.

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Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire

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In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy CMeans methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc.).

Keywords: Defuzzification, floating search, fuzzy clustering, Zernike moments.

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Authors: Ali Alzaabi, Georges Alquié, Hussain Tassadaq, Ali Seba

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This article presents the developments of efficient algorithms for tablet copies comparison. Image recognition has specialized use in digital systems such as medical imaging, computer vision, defense, communication etc. Comparison between two images that look indistinguishable is a formidable task. Two images taken from different sources might look identical but due to different digitizing properties they are not. Whereas small variation in image information such as cropping, rotation, and slight photometric alteration are unsuitable for based matching techniques. In this paper we introduce different matching algorithms designed to facilitate, for art centers, identifying real painting images from fake ones. Different vision algorithms for local image features are implemented using MATLAB. In this framework a Table Comparison Computer Tool “TCCT" is designed to facilitate our research. The TCCT is a Graphical Unit Interface (GUI) tool used to identify images by its shapes and objects. Parameter of vision system is fully accessible to user through this graphical unit interface. And then for matching, it applies different description technique that can identify exact figures of objects.

Keywords: Harris Extraction and SIFT Matching

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Authors: Mejía M. Paula, Ramírez L. Leonardo, Puerta A. Gabriel

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In telemedicine, the image repository service is important to increase the accuracy of diagnostic support of medical personnel. This study makes comparison between two routing algorithms regarding the quality of service (QoS), to be able to analyze the optimal performance at the time of loading and/or downloading of medical images. This study focused on comparing the performance of Tabu Search with other heuristic and metaheuristic algorithms that improve QoS in telemedicine services in Colombia. For this, Tabu Search and Simulated Annealing heuristic algorithms are chosen for their high usability in this type of applications; the QoS is measured taking into account the following metrics: Delay, Throughput, Jitter and Latency. In addition, routing tests were carried out on ten images in digital image and communication in medicine (DICOM) format of 40 MB. These tests were carried out for ten minutes with different traffic conditions, reaching a total of 25 tests, from a server of Universidad Militar Nueva Granada (UMNG) in Bogotá-Colombia to a remote user in Universidad de Santiago de Chile (USACH) - Chile. The results show that Tabu search presents a better QoS performance compared to Simulated Annealing, managing to optimize the routing of medical images, a basic requirement to offer diagnostic images services in telemedicine.

Keywords: Medical image, QoS, simulated annealing, Tabu search, telemedicine.

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Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang

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Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA.

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Authors: V. K. Ananthashayana, Jyothirmayi M.

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This paper addresses the problem of source separation in images. We propose a FastICA algorithm employing a modified Gaussian contrast function for the Blind Source Separation. Experimental result shows that the proposed Modified Gaussian FastICA is effectively used for Blind Source Separation to obtain better quality images. In this paper, a comparative study has been made with other popular existing algorithms. The peak signal to noise ratio (PSNR) and improved signal to noise ratio (ISNR) are used as metrics for evaluating the quality of images. The ICA metric Amari error is also used to measure the quality of separation.

Keywords: Amari error, Blind Source Separation, Contrast function, Gaussian function, Independent Component Analysis.

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Authors: H. B. Kekre, Kavita Patil

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This paper describes a novel and effective approach to content-based image retrieval (CBIR) that represents each image in the database by a vector of feature values called “Standard deviation of mean vectors of color distribution of rows and columns of images for CBIR". In many areas of commerce, government, academia, and hospitals, large collections of digital images are being created. This paper describes the approach that uses contents as feature vector for retrieval of similar images. There are several classes of features that are used to specify queries: colour, texture, shape, spatial layout. Colour features are often easily obtained directly from the pixel intensities. In this paper feature extraction is done for the texture descriptor that is 'variance' and 'Variance of Variances'. First standard deviation of each row and column mean is calculated for R, G, and B planes. These six values are obtained for one image which acts as a feature vector. Secondly we calculate variance of the row and column of R, G and B planes of an image. Then six standard deviations of these variance sequences are calculated to form a feature vector of dimension six. We applied our approach to a database of 300 BMP images. We have determined the capability of automatic indexing by analyzing image content: color and texture as features and by applying a similarity measure Euclidean distance.

Keywords: Standard deviation Image retrieval, color distribution, Variance, Variance of Variance, Euclidean distance.

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Authors: F. C. Calnegru

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This article presents a computationally tractable probabilistic model for the relation between the complex wavelet coefficients of two images of the same scene. The two images are acquisitioned at distinct moments of times, or from distinct viewpoints, or by distinct sensors. By means of the introduced probabilistic model, we argue that the similarity between the two images is controlled not by the values of the wavelet coefficients, which can be altered by many factors, but by the nature of the wavelet coefficients, that we model with the help of hidden state variables. We integrate this probabilistic framework in the construction of a new image registration algorithm. This algorithm has sub-pixel accuracy and is robust to noise and to other variations like local illumination changes. We present the performance of our algorithm on various image types.

Keywords: Complex wavelet transform, image registration, modeling using hidden state variables, probabilistic similaritymeasure.

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