• F6_249750
  • 1.3MB
  • rar
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  • VIP专享
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  • 2022-05-20 08:56
虹膜识别源码 public class Main { public Main(String filename) { System.out.println("\n\n\tIris Recognition\n\t(c)2004 Richard Midwinter\n\n"); System.out.println("Reading image..."); File file = new File(filename); if (file.exists()) { System.out.println("Image located..."); } else { System.out.println("Error! Check you've specified the correct path to the image and you have the permissions to view it"); System.exit(1); } BufferedImage bimg = null; try { bimg =; /* Segmentation code */ Segment segment = new Segment(); segment.segment(bimg); /* Normal encoding */ /* Feature encoding */ } catch (Exception e) { System.out.println(e); } } public static void main(String[] args) { if (args.length != 1) System.out.println("Usage: java Main filename.jpg"); else new Main(args[0]); } private BufferedImage bimg; }
  • JIRRM - An iris recognition project in Java_files
  • overview.png
  • project-support.jpg
  • style.css
  • jirrm-src-0.0.2.tar.gz
  • JIRRM - An iris recognition project in Java.htm
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"> <html><head> <meta http-equiv="Content-Type" content="text/html; charset=ISO-8859-1"> <title>JIRRM - An iris recognition project in Java</title> <link rel="stylesheet" href="JIRRM%20-%20An%20iris%20recognition%20project%20in%20Java_files/style.css" type="text/css"> </head><body> <div id="menu"> <ul><li><a href="" rel='nofollow' onclick='return false;'>home</a> | <a href="" rel='nofollow' onclick='return false;'>about</a> | <a href="" rel='nofollow' onclick='return false;'>documentation</a> | <a href="" rel='nofollow' onclick='return false;'>download</a> | <a href="" rel='nofollow' onclick='return false;'>screenshots</a> | <a href=";atid=699978" rel='nofollow' onclick='return false;'>support</a></li></ul> </div> <div class="content"> <p><strong>JIRRM</strong> is an open source iris recognition software package written in Java. It comes with a single backend library and several front ends, obtainable as a single package or separately. </p><p> We are currently working on developing the main library and new ways to integrate the technology with existing software.</p> <p>Overview of backend design:<br><br><a href="" rel='nofollow' onclick='return false;'></a></p> <p><strong>Segmentation:</strong><br><br> Done: The image is cleaned up and a circular Hough transform is used to isolate the inner and outer iris boundaries.<br>Todo: Advance the algorithm to ensure the inner boundary is within 20-90% of the outer boundary. Automatically choose the iris and pupil boundary radii. </p> <p><strong>Normalisation and feature encoding:</strong><br><br> Done: Basic rubber mapping. Need to account for pupil and iris boundaries not being quite concentric.<br>Todo: Fully implement rubber sheet mapping - converting the disc of the iris to a rectangular matrix. Remove occlusions - the eyelashes, the eyelids, specular reflections.</p> <p><strong>Matching:</strong><br><br> Done: Planning.<br> Todo: Extract an iriscode which maximises differences. Perhaps using Principle Components Analysis, or potentially a choice of several algorithms.</p> <p><strong>Front ends to the project:</strong><br><br> We have a limited SWT frontend. It needs much development, some of which is likely to take place as backend development and testing occurs. There is scope to develop third party plugins, eg. for xlock.</p> <a href="" rel='nofollow' onclick='return false;'></a> </div> <div class="footer"> <p><a href="" rel='nofollow' onclick='return false;'>jirrm</a></p> </div> </body></html>