IJIGSP Vol. 8, No. 5, May. 2016
Cover page and Table of Contents: PDF (size: 184KB)
Human Skin detection is one of the most widely used algorithms in vision literature which has been numerously exploited both directly and indirectly in multifarious applications. This scope has received a great deal of attention specifically in face analysis and human detection/tracking/recognition systems. As regards, there are several challenges mainly emanating from nonlinear illumination, camera characteristics, imaging conditions, and intra-personal features. During last twenty years, researchers have been struggling to overcome these challenges resulting in publishing hundreds of papers. The aim of this paper is to survey applications, color spaces, methods and their performances, compensation techniques and benchmarking datasets on human skin detection topic, covering the related researches within more than last two decades. In this paper, different difficulties and challenges involved in the task of finding skin pixels are discussed. Skin segmentation algorithms are mainly based on color information; an in-depth discussion on effectiveness of disparate color spaces is elucidated. In addition, using standard evaluation metrics and datasets make the comparison of methods both possible and reasonable. These databases and metrics are investigated and suggested for future studies. Reviewing most existing techniques not only will ease future studies, but it will also result in developing better methods. These methods are classified and illustrated in detail. Variety of applications in which skin detection has been either fully or partially used is also provided.[...] Read more.
The objective of this study is to propose a new method for text region localization and character extraction in natural scene images with complex background. In this paper, a hybrid methodology is suggested which extracts multilingual text from natural scene image with cluttered backgrounds. The proposed approach involves four steps. First, potential text regions in an image are extracted based on edge features using Contourlet transform. In the second step, potential text regions are tested for text content or non-text using GLCM features and SVM classifier. In the third step, detection of multiple lines in localized text regions is done and line segmentation is performed using horizontal profiles. In the last step, each character of the segmented line is extracted using vertical profiles. The experimentation has been done using images drawn from own dataset and ICDAR dataset. The performance is measured in terms of the precision and recall. The results demonstrate the effectiveness of the proposed method, which can be used as an efficient method for text recognition in natural scene images.[...] Read more.
Matched and mismatched filters are considered important parts of a radar signal processing unit. In this paper, we present an approach to optimize the matched filters and mismatched filters in short range pulse radars. For radar, the matched filter coefficients are the complex conjugates of transmitted code. We used binary phase codes as transmitted pulse. The disadvantage of binary phase codes is having high sidelobe levels in the output of correlation function. Thus, we decided to use optimization algorithms for finding binary phase codes with minimum peak sidelobe levels (MPS). After that, we succeeded in producing mismatched filter coefficients (Mis-co) for each code using floating point genetic algorithm (FGA) and we could generate and test the filter coefficients with maximum peak to sidelobe level ratio (PSR). For testing the filter, we plotted ambiguity function for each set of coefficients and tested the filter with Doppler shift.[...] Read more.
In synthetic aperture radar (SAR) imaging, the transmitted microwave pulses from space born antenna interacts with ground objects and returned energy or back scattered energy will be collected to get backscattered image. In SAR image processing, a not anticipated noise (speckle noise) is added due to the coherent imaging system, which makes the image analysis troublesome. For better SAR image processing, the noise is to be removed or minimized in the begging stages of pre-processing and texture features are to be effectively maintained. The wavelet based Block Matching 3D (BM3D) method is normally considered as the state of art technique in the area of denoising of images. This method generally depends on up and down sampling conversion. In this paper, it is proposed a denoising technique which is independent on sampling conversion, so that texture features can be maintained, in which the speckle noise is reduced to the maximum extent.[...] Read more.
The distribution of multimedia has revolutionized the web technology at very fast pace. Duplication of computerized information are created and conveyed through the web technology. Unlawful acts, for example, tampering, forging, copyright isolations and frauds on multimedia data are becoming very common in the society. Digital watermarking is one such innovation that has been produced to shield multimedia data from illegal manipulations. The advancement of technical solutions in view of watermarking method for copyright assurance has been a subject of active research amid the most recent decade. In this paper, hybridization Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) using redundant wavelet is proposed for robust digital video watermarking. The results of combining the two transform using redundant wavelets shows that the performance of proposed video watermarking scheme is enhanced and satisfies the requirement of imperceptibility. The presented results also showed that the scheme has the capacity to withstand an assortment of video processing attacks.[...] Read more.
Authorship attribution is one of the important problem, with many applications of practical use in the real-world. Authorship identification determines the likelihood of a piece of writing produced by a particular author by examining the other writings of that author. Most of the research in this field is carried out by using instance based model. One of the disadvantages of this model is that it treats the different documents of each author differently. It produces a matrix per each document of the author, thus creating a huge number of matrices per author, i.e. the dimensionality is very high. This paper presents authorship identification using Author based Rank Vector Coordinates (ARVC) model. The advantage of the proposed ARVC model is that it integrates all the author's profile documents into a single integrated profile document (IPD) and thus overcomes the above disadvantage. To overcome the ambiguity created by common words of authors ARVC model removes the common words based on a threshold. Singular value decomposition (SVD) is used on IPD after removing the common words. To reduce the overall dimension of the matrix, without affecting its semantic meaning a rank-based vector coordinates are derived. The eigenvector features are derived on ARVC model. The present paper used cosine similarity measure for author attribution and carries out authorship attribution on English poems and editorial documents[...] Read more.
Visual surveillance System is used for analysis and interpretation of object behaviors. It involves object classification to understand the visual events in videos. In this review paper various object classification methods are used. Classification technique plays an important role in surveillance system that is used for the classification of both objects like static and moving objects in a better way. The methods in object classification are used to extract meaningful information and various features that are needed for representation of data. In this survey, we described various approaches for moving objects that are used in classification for video surveillance system based on shape and motion.[...] Read more.
Imaging techniques are used to create images of structure, function and pathology of human body organs for cancer diagnosis. Various imaging techniques like X-ray, Ultra-Sonography (US), Positron Emission Tomography (PET), Ultrasound, MRI etc. are used for cancer diagnosis. These imaging techniques have gone through Lot of advancements during lost few years. These techniques vary in the technology and application. Various artifacts exist in these imaging techniques and images produced by theses imaging techniques. These artifacts can be exploited to enhance the imaging technique and the images produced by them.[...] Read more.