sIris Recognition Algorithms Based on Texture Analysis
نویسندگان
چکیده
Iris recognition has become a popular research in recent years due to its reliability and nearly perfect recognition rates. Iris recognition system has three main stages: image preprocessing, feature extraction and template matching. An innovative method is proposed to extract iris features based on texture analysis. Iris textures are analyzed to capture the discriminating frequency information. Specific filters with different center frequency are applied to three different zones to extract the texture of the iris. Different weightings are given to each zone depending on its contribution to the recognition. The encoded binary templates are compact in size and can avoid the visibility of the individual iris images. The templates are suitable for implementing iris recognition devices using DSP (Digital Signal Processor). The proposed method was evaluated using CASIA iris image database version 1.0 [1]. Experimental results show that the proposed approach has achieved high accuracy of 98.62%.
منابع مشابه
Second-Order Statistical Texture Representation of Asphalt Pavement Distress Images Based on Local Binary Pattern in Spatial and Wavelet Domain
Assessment of pavement distresses is one of the important parts of pavement management systems to adopt the most effective road maintenance strategy. In the last decade, extensive studies have been done to develop automated systems for pavement distress processing based on machine vision techniques. One of the most important structural components of computer vision is the feature extraction met...
متن کاملOn the use of Textural Features and Neural Networks for Leaf Recognition
for recognizing various types of plants, so automatic image recognition algorithms can extract to classify plant species and apply these features. Fast and accurate recognition of plants can have a significant impact on biodiversity management and increasing the effectiveness of the studies in this regard. These automatic methods have involved the development of recognition techniques and digi...
متن کاملFacial Expression Recognition Based on Anatomical Structure of Human Face
Automatic analysis of human facial expressions is one of the challenging problems in machine vision systems. It has many applications in human-computer interactions such as, social signal processing, social robots, deceit detection, interactive video and behavior monitoring. In this paper, we develop a new method for automatic facial expression recognition based on facial muscle anatomy and hum...
متن کاملPerformance Evaluation of Image Segmentation and Texture Extraction Methods in Scene Analysis
The main aim of this thesis is to evaluate the performance of image segmentation and texture analysis algorithms on synthetic and real images. As a part of this study, two popular texture benchmarks called MeasTex and VisTex have been used. A new scene analysis benchmark, called PANN database, has been generated as a part of this study for the evaluation of image analysis tools on natural objec...
متن کاملSeveral pattern recognition approaches for region-based image analysis
The objective of this paper is to describe some pattern recognition approaches for image segmentation. First, in the introduction, we present the general aspects of omogenity and texture recognition. Then we provide a mean-based feature extraction approach for uniformity analysis and a moment-based one for texture analysis. In the classification stage we propose both supervised and also unsuper...
متن کامل