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This paper proposed a new approach for inner-knuckle-print recognition. Theinner knuckle print is one of the reliable physiological characteristics among different approaches that exist in biometric. In this paper, the image of the inner surface of the middle and ring fingers are used for human verification. We considered the inner knuckle print as a texture and applied two types of feature extraction...
In recent years, there has been significant work in effective recognition of human facial expression. In this paper, we consider a new method for facial expression recognition, based on structural differences. The differences are regulated based on comprehensive laws for every expression. This article uses the Fuzzy Nero algorithm to classify support machines that have close fuzzy separation. With...
The diagnosis of disease with the aid of computer programs has been developing more and more in recent years. This paper presents an approach which is based on frequency technique for the objective quantitative analysis of facial paralysis. In this method, limited-orientation modified circular Gabor filters (LO-MCGFs) are used to enhance the desirable frequencies in images. Then, features are extracted...
Face recognition is a quintessential biometric technique. It still remains challenging to accurately characterize the identity related features in face images. In this paper, we propose a novel classification method based on Kernel Fisher Discriminant Analysis using the distinctiveness of Gabor features and the robustness of ordinal measures. These parameters are derived from magnitude, phase, real...
Glaucoma at the later stages causes eye blindness, it is essential for early detection to minimize the risks and warn patients who might eventually lose their vision. The study gives an assessment on Glaucoma detection using the Histogram of Oriented Gradients (HOG) Feature extraction along with SVM classification of retinal fundus image with the extraction of blood vessels using Gabor filter. Retinal...
Image Segmentation plays an important role in image processing as it is at the foundation of many high-level computer vision tasks, such as scene understanding and object recognition. In this paper, an adaptive growing and merging algorithm is proposed to segment an image accurately. First, mean shift is applied to produce superpixels, and then superpixels grow according to their lab histograms and...
Text detection in natural scenes holds great importance in the field of research and still remains a challenge because of size, various fonts, line orientation, different illumination conditions, weak character and complex background in image. The contribution of the proposed method is filtering out complex backgrounds by utilizing two masks filtering based on text confidence map in the first step...
A Multi-biometric System amalgamates the evidences collected from the multiple sources or single source for person recognition based on templates like fingerprint, palm print and iris. These evidences can be combined at various levels like pixel level, score level, feature level, and decision level. A rich set of information is present at feature level, but there is a problem of dimensionality which...
This paper compares four methods of feature extraction: Fractional Eigenfaces and Vander Lugt Correlator as global methods, and Gabor Ordinal Measures and Uniform Local Binary Pattern as local ones. We evaluate the four methods on the standard FERET probe data sets in order to study the robustness of these techniques against illumination variation, facial expression variation and aging. The Gabor...
In order to accurately detect the patterned fabric defects, a novel patterned fabric detection algorithm based on Gabor-HOG (GHOG) and low-rank recovery is proposed. Firstly, Gabor filter preprocess the pattern fabric image to generate the Gabor maps, and then HOG feature is extracted from the blocks of Gabor maps with size of 16×16. Secondly, the feature vectors GHOG of all blocks is stacked into...
Several efforts are being made in studying sleeping posture of a person under natural conditions without causing discomfort. In this study, various methods are proposed and explored in which features defining sleep postures of a person are investigated for intelligent pattern recognition. Using the measured depth data, three dimensional depth scans as well as the cross-sectional scans of the static...
Texture analysis has been an important research area due to wide range of applications in the field of image processing, machine vision and pattern recognition. In this paper, we present a comprehensive analysis of texture descriptors for texture classification. We focus on state of the art texture descriptors which have been widely used for classification in literature and shown promising results...
The purpose of this study is to develop a texture-based algorithm for breast cancer classification in Thermography and performance evaluation for the purposed method. The aim of screening a disease is early detection in order to decrease the rate of mortality. CAD systems can be reckonable diagnostic tools for this importance and Infra-red imaging is expressed as a portable, non-invasive, non-contact...
Classification of soil is the dissolution to soil sets to particular group having a like characteristics and similar manners. Almost all countries do product exporting, in which those countries exporting higher agricultural product are very much depend on the soil characteristics. Thus, soil characteristics identification and classification is very much important. Identification of the soil type helps...
Minutiae-based fingerprint matching methods suffer difficulty in automatically extracting all minutiae points due to failure to detect the complete ridge structures of a fingerprint, as well as describing all the local ridge structures as minutiae points. These make matching a difficult process for example, the case where two fingerprints have different numbers of uncaptured minutiae points and hence...
Faces express many social indications, including gender, ethnicity, age, expression and identity, most of them have drawn thriving attention from various research communities, for instance neuroscience, computer science and psychology. In this paper, we propose a new approach to classify gender and ethnicity by merging both texture and shape features extracted from face images. Gabor filter is used...
The sign language considered as the main language for deaf and dumb people. So, a translator is needed when a normal person wants to talk with a deaf or dumb person. In this paper, we present a framework for recognizing Bangla Sign Language (BSL) using Support Vector Machine. The Bangla hand sign alphabets for both vowels and consonants have been used to train and test the recognition system. Bangla...
Computer-aided diagnosis (CAD) technology can improve the detection of abnormal. Such as calcifications, masses, and architectural distortion. Among the three abnormals, architectural distortion is the most difficult one to detect for both radiologists and CAD systems. In this article, we use automatic architectural distortion detection method to locate initial suspicious areas. Then, combine the...
This paper presents an audio event classification algorithm which automatically classifies an audio event as footstep, glass breaking, gunshot or scream mainly for surveillance applications. First, the Gabor feature of the audio spectrogram is extracted, there are two kinds of Gabor features, namely global Gabor feature and local Gabor feature. Then we use Principal Components Analysis (PCA) and Linear...
Zebra-crossing region detection from a zebra-crossing image is a challenging activity to support visually impaired navigating safely in outdoor environments. This paper proposes a zebra-crossing detection framework based on unique geometrical features of zebra-crossing. The unique geometrical feature is zebra-crossing stripe's edges are arranged in sorted order. Initially, pre-process the zebra-crossing...
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