tailieunhanh - The application of cellular learning automata in individuals

In this method, cells show a complex behavior by interacting with each other. Image features involving edges, lines, borders and etc can be extracted in machine sight and image processing by using some mathematics operations sight and image processing by using mathematics operations such as edge detection by gradient or by through applying suitable filters. By extracting these features, processing area can be segmented with higher precision. Cellular learning automata can be applied in terms of edge and border detection. | International Journal of Computer Networks and Communications Security VOL. 3, NO. 5, MAY 2015, 200–204 Available online at: E-ISSN 2308-9830 (Online) / ISSN 2410-0595 (Print) The Application of Cellular Learning Automata in Individuals' Identification on the Basis of iris Image Msc. NADER CHAHARDAH CHERICKI GHORBANI1, 2 and PhD. HAMID HAJ SEYYED JAVADI3 1 Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Boroujerd, Iran 2 3 Department of Computer Engineering, Boroujerd Branch, Islamic Azad University, Boroujerd, Iran Department of Applied Mathematics, Faculty of Mathematics and Computer Science, Shahed University, Tehran, Iran E-mail: 1, 2 , ABSTRACT Using biometric methods is one of the methods widely used for individuals' identification. In this system, unique characteristics of individuals are used such as fingerprint, face recpgnition, image detection of iris or retinal, the form of ears and complex tissue, and the part nearer to pupil is called crinkle part. This area has an intensive tissue placed near to each other. An identification system on the basis of iris involves four steps as follows: step 1: getting the image and pre-processing, step 2: Segmentation, step 3: Normalization, step 4: features and characteristics extraction, and step 5: adaptation and Classification. Pre-processing step involves three steps such as zoning, normalization and recovery. In this study, the application of cellular learning automata is studied in image pre-processing constituted of simple components, and the behavior of each element and component is determined and improved on the basis of neighbors behavior and previous experiences. In this method, cells show a complex behavior by interacting with each other. Image features involving edges, lines, borders and etc can be extracted in machine sight and image processing by using some mathematics operations sight and .