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Bonfring International Journal of Advances in Image Processing

Journal Papers (18) Details Call for Paper Manuscript submission Publication Ethics Contact Authors' Guide Line
1 Ensuring Security to the Compressed Sensing Data Using a Steganographic Approach, A.V. Sreedhanya and K.P. Soman
This paper focuses on the strength of combining cryptography and steganography methods to enhance the security of communication over an open channel. Here the data to be send are secured by using the compressive sensing method and the Singular Value Decomposition (SVD) based embedding method. The data is encrypted using the compressive measurements of the data and the resultant data is embedded in the cover object using the SVD based water mark embedding algorithm. This approach helps to send the secret data after hiding in a cover image. The compressive sensing method helps to compress and encrypt the data in a single step. The proposed system provides more security to the compressed data. This scheme significantly reduces the attacks. This method is very useful to hide the secret images. The results demonstrate that the proposed system is highly efficient and robust.
2 Buried Object Discrimination in a Ground Penetrating Radar Radargram, M.P. Priyadarshini and Dr.G. Indumathi
Ground Penetrating Radar (GPR) is a non-destructive technique used for the location of objects or interfaces buried beneath the earth's surface or located within a visually opaque structure. This research work proposes techniques for buried object discrimination for the images generated by GPR by using GPR frequency-domain spectral features. The motivation for this approach comes from the fact that landmine targets and clutter objects often have different shapes and/or composition, yielding different Energy Density Spectrum (EDS) that may be exploited for their discrimination. The proposed system comprises cascade of two stages: Pre - Processing Stage, followed by Discrimination Stage. Pre Processing eliminates the ground bounce and clutter to get an enhanced image. Enhancement is followed by Landmine or clutter Discrimination using Energy Density Spectrum. All implementations are done using MATLAB.
3 An Efficient CBIR Approach for Diagnosing the Stages of Breast Cancer Using KNN Classifier , Jini.R. Marsilin and Dr.G. Wiselin Jiji
This paper proposes a mammogram image retrieval technique using pattern similarity scheme. Comparing previous and current mammogram images associated with pathologic conditions are used to diagnose the real stage of breast cancer by doctors. Lack of awareness and screening programs causes the breast cancer deaths. Early detection is the best way to reduce the deaths per incident ratio. Mammogram is the best one in the currently used technique for diagnosing breast cancer. In this paper, the retrieval process is divided into four distinct parts that are feature extraction, kNN classification, pattern instantiation and computation of pattern similarity. In feature extraction step, low level texture features like entropy, homogeneity, contrast, energy, correlation and run length matrix features are extracted. These extracted features are classified using K-Nearest Neighbor classifier to differentiate the normal tissue from abnormal one. Each group is considered as patterns. Finally, pattern similarity is estimated for retrieving images based on their similarity with the query image. This scheme is effectively applied to the Content Based Image Retrieval systems to retrieve the images from large databases and identify the real stage of breast cancer. If we find cancer in early stages we can cure it.
4 A Detailed Survey on Various Image Inpainting Techniques , V. Janarthanan and G. Jananii
Inpainting, the technique of transform an image in an imperceptible form, is as past as art itself. The main objective of inpainting is from the reinstallation of damaged paintings and photographs to the elimination of chosen objects. Image Inpainting is used to filling the misplaced or smashed region in an image make use of spatial information of its neighbouring region. Inpainting algorithm have numerous applications. It is attentively used for restoration of older films and object removal in digital photographs. It is also useful to red-eye correction, compression etc. The objective of the Inpainting is to change the damaged region in an image in which the inpainted region is invisible to the common observers who are not familiar with the original image. There have been quite a few approaches are proposed for the image inpainting techniques. This proposed work presents a brief survey of different image inpainting techniques and relative study of these techniques. In this paper provide an analysis of different techniques used for image Inpainting. Finally a best inpainting technique is suggested in this paper.
5 Spectral Recognition Techniques and MLC of IRS P6 LISS III image for Coastal Landforms Extraction along South West Coast of Tamilnadu, India , S. Kaliraj and N. Chandrasekar
The Remote sensing technology is measured or observed reflected energy to construct an image of the landscape beneath the platform passage in a discrete pixel format. The geometric and radiometric characteristics of remotely sensed image provide information about earth's surface. In the present study, the primary data product obtained from IRS P6 satellite LISS - III images (23.5 m) are used to extract the landforms the South West coast of Tamil nadu, India. The study area comprises different types of landforms in nature. The selected image processing techniques are employed such as, geometric correction, radiometric correction for removal of atmospheric errors and noise from image and to identify spectral and spatial variations in structure, texture, pattern of objects in the image. Here, the spectral recognition statistics namely edge detection; edge enhancement; histogram equalization, principal component analysis and maximum likelihood classifier algorithms are applied for demarcate the coastal landforms. In the maximum likelihood classification process, the spectral properties (Digital Number) of an object (kn) in the image has been identified using mean and covariance of pixels in training set, then the probability function (Px) determines the distribution of that group of pixels (class) in the image. The coastal landforms are segmented as separate class from the image based on their spectral and spatial characteristics such as shoreline, beach, sand dunes, erosional and accretion lands, water body, river deltas, and manmade infrastructure with attribute of shape, area, location and spatial distribution.
6 FPGA based Implementation of Embedding and Decoding Architecture for Binary Watermark by Spread Spectrum Scheme in Spatial Domain , Sudip Ghosh, Somsubhra Talapatra, Navonil Chatterjee, Santi P Maity and Hafizur Rahaman
With the increasing influence of digital network and communication, armour from perilous intrusion and corruption of information (e.g. image, video, speech etc) during transmission is a paramount issue. To protect the image and video from the unauthenticated access or tampering, watermarking is adopted as a solution. In this paper we have proposed a spatial domain Spread Spectrum (SS) watermarking scheme using binary watermark which effectively eliminates security problem while increasing robustness and enhancing perceptual quality of watermarked image. Hardware implementation of the proposed digital image watermarking algorithm using Field Programmable Gate Array (FPGA) has been accomplished.
7 Compression of Medical Images by Prediction on Wavelet Transform Coefficients , P.S. Arya Devi and M.G. Mini
Compression of medical image is a challenging task as the compression has to be achieved without losing diagnostic quality of the images. Reducing the size of image finds its application in saving storage space and increasing transmission speed, as in case of teleradiology. On the decomposed details of an image, prediction is done. The high SNR (Signal to Noise ratio) and localization provided by wavelet coefficients makes it suitable for images. With few prediction coefficients, as small as 15, the whole image is reconstructed. The four variants of the method are studied to find its suitability for different types of images. The method is evaluated using various objective fidelity criteria.
8 Ensuring Security to the Compressed Sensing Data Using a Steganographic Approach , A.V. Sreedhanya and K.P. Soman
This paper focuses on the strength of combining cryptography and steganography methods to enhance the security of communication over an open channel. Here the data to be send are secured by using the compressive sensing method and the Singular Value Decomposition (SVD) based embedding method. The data is encrypted using the compressive measurements of the data and the resultant data is embedded in the cover object using the SVD based water mark embedding algorithm. This approach helps to send the secret data after hiding in a cover image. The compressive sensing method helps to compress and encrypt the data in a single step. The proposed system provides more security to the compressed data. This scheme significantly reduces the attacks. This method is very useful to hide the secret images. The results demonstrate that the proposed system is highly efficient and robust.
9 Buried Object Discrimination in a Ground Penetrating Radar Radargram , M.P. Priyadarshini and Dr.G. Indumathi
Ground Penetrating Radar (GPR) is a non-destructive technique used for the location of objects or interfaces buried beneath the earth's surface or located within a visually opaque structure. This research work proposes techniques for buried object discrimination for the images generated by GPR by using GPR frequency-domain spectral features. The motivation for this approach comes from the fact that landmine targets and clutter objects often have different shapes and/or composition, yielding different Energy Density Spectrum (EDS) that may be exploited for their discrimination. The proposed system comprises cascade of two stages: Pre - Processing Stage, followed by Discrimination Stage. Pre Processing eliminates the ground bounce and clutter to get an enhanced image. Enhancement is followed by Landmine or clutter Discrimination using Energy Density Spectrum. All implementations are done using MATLAB.
10 Convergence of Optimization Problems , K. Jeyalakshmi
In this paper we consider a general optimization problem (OP) and study the convergence and approximation of optimal values and optimal solutions to changes in the cost function and the set of feasible solutions. We consider the convergence optimization problems under the familiar notion of uniform convergence. We do not assume the convexity of the functions involved. Instead we consider a class of functions whose directional derivatives are convex. They are known as locally convex functions or following Craven and Mond nearly convex functions. We given necessary preliminaries and we prove that a sequence of locally convex optimization problems converge to a locally convex problem. We also prove that uniform convergence of locally convex optimization problems implies epi-graph convergence of the problems. Even though for simplicity we have taken locally convex functions, the results given here can be proved for locally Lipchitz functions also.
11 Convergence of Optimization Problems , K. Jeyalakshmi
In this paper we consider a general optimization problem (OP) and study the convergence and approximation of optimal values and optimal solutions to changes in the cost function and the set of feasible solutions. We consider the convergence optimization problems under the familiar notion of uniform convergence. We do not assume the convexity of the functions involved. Instead we consider a class of functions whose directional derivatives are convex. They are known as locally convex functions or following Craven and Mond nearly convex functions. We given necessary preliminaries and we prove that a sequence of locally convex optimization problems converge to a locally convex problem. We also prove that uniform convergence of locally convex optimization problems implies epi-graph convergence of the problems. Even though for simplicity we have taken locally convex functions, the results given here can be proved for locally Lipchitz functions also.
12 On ? - generalized ? - Continuous Mappings in Topological Spaces , N. Kalaivani and G. Sai Sundara Krishnan
In this paper we introduce the concept of On ? - generalized ? - Continuous Mappings in Topological Spaces and study its relationship with other mappings. Further we declare the concepts of ?-? continuous mappings and ? -g ? continuous mappings which coincide when the space is ?-? T-1/2. In addition, we define the concept of ? -g ?-irresolute mappings in topological spaces; also we attain the relationships between ? -g ?-continuous and ? -g ?-irresolute mappings and obtain some of its basic properties.
13 Edge Detection Using Fuzzy Double Gradient Morphology, Dillip Ranjan Nayak
Detecting the edges of objects within images is a critical task for quality image processing. This paper proposes an edge detection operator based on the combination of fuzzy gradient morphology and Sobel operator. When we use traditional detection operators to detect the edge of an object in an image, we get lots of noisy Points. In this paper, we demonstrate a technique in which we preprocess an image with Sobel operator and then apply gradient morphology. This method effectively removes the noise and gives good detail image edge detection. We evaluate the method quantitatively and compare it to classical morphological method. Our fuzzy based edge segmentation method performs better than the classical edge detectors. Since the proposed methods are based on fuzzy morphological operations, these are efficient and enhanced
14 Image Analysis of Suzaku Observation of Transient Pulsar EXO 2030+375, Animesh Basak and Tamal Sarkar
EXO 2030+375 is a well-known binary system showing periodic outburst. The spectral analysis on the system during the outburst helps us to know more about the origin as well as material present within the system. In this work, we have considered one such outburst data obtained using Suzaku X-Ray mission having very good imaging as well as energy resolution capabilities. Following the stepwise algorithm of the Suzaku analysis guide, we have applied the various computational modules for pre-processing as well as data reduction. After that, we have used the ftools, a specialized computational package for analysis of X-ray data obtained from various X-Ray missions. The data analysis helped us to understand the origin as well as given an insight of the material present within the system
15 De-blurring Cardiac SPECT Images by Maximum Likelihood Approach, Neethu M. Sasi and Jayasree V.K.
This paper presents a blind de-convolution algorithm for enhancing cardiac SPECT images by reducing the blur present in the image. The method is based on maximum likelihood estimate and in particular, the processing is done in a suitable color space. An iterative algorithm, without any prior information, is used to estimate the original image and the point spread function. Blur metric and peak signal to noise ratio are considered for performance evaluation of the algorithm. The effect of number of iterations on the quality of de-blurred image is also studied. Real medical images are used for appraising the algorithm
16 Altered Fingerprint Matching Using Ridge Texture and Frequency in the Unaltered Region, T.R. Anoop and M.G. Mini
Fingerprint alteration is the process of changing the regularly spaced ridge structure by mechanical or chemical means to hide the identity from Automated Fingerprint Identification System. This paper presents a method for altered fingerprint matching using texture and ridge frequency in the unaltered region. Wavelet transform is used to create feature vectors from ridge frequency and ridge texture. Matching score obtained for both texture and ridge frequency is fused together to obtain final score. Results of one to many matching between synthetically altered fingerprints and its unaltered mates shows that this method is suitable for altered fingerprint matching
17 ParQuoSCI: Pseudorandom Partial Quotient Sequences for Content based Image Authentication, Jayashree S Pillai and T. Padma
The application of a number theory based pseudorandom sequence called Partial Quotient (PQ) sequence generated from the continued fraction expansion of irrational numbers in a semi fragile watermarking scheme for content based image authentication is considered in this paper. The generated pseudorandom PQ sequence is used to create sub vectors to be used at various instances in the watermarking process. The watermark is derived from the image and is embedded in the higher textured blocks. The watermarked images demonstrate high imperceptibility and make it suitable for use in artistic, medical and military applications where high quality and minimal distortion of the watermarked images is required
18 MRI Brain Image Enhancement Using XILINX System Generator and DWT, Gouri B. Deshpande and Dr.K. Ramesha
This paper presents a novel method of enhancing the image quality of human brain obtained from Magnetic Resonance Imaging scans. Here, we are trying to enhance the brain image using Xilinx System Generator, which is a DSP tool devised by Xilinx Corporation. The architecture presented in this paper utilizes a graphical user interface that bands together MATLAB Simulink and XSG offering appropriate hardware implementation. Hence, the quality of image is improved. These images are, then, fed to artificial neural network, for normality or abnormality classification of brain. This paper utilizes ANN using multiperceptron and back propagation method. This method first makes use of discrete wavelet transform to extract energy values from enhanced images using filters and then it is fed to ANN for further classification. The image enhancement using XSG, has its performance measured in terms of resource utilization by using FPGA XC5VLX50T is also measured