Dissertation > Excellent graduate degree dissertation topics show

Research on the Key Technology of Iris Recognition

Author: WangLiangHui
Tutor: LiuAnZhi
School: National University of Defense Science and Technology
Course: Electronic Science and Technology
Keywords: Iris Recognition Iris Location Image preprocessing Standardization Feature Extraction Pattern Matching
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 15
Quote: 0
Read: Download Dissertation

Abstract


With the development of modern information technology, the traditional method of identification has been unable to meet the security needs of today's society, and authentication method based on biometric smart to get great concern. Compared with other biometrics, iris recognition has uniqueness, stability, non-invasive and non-forged such advantages. In recent years, the iris recognition technology has achieved great development, and has a wide range of applications in many fields. The iris recognition system consists mainly of four parts iris image acquisition, image preprocessing, feature extraction and pattern matching. The paper focuses on the key to iris recognition technology: the border of the iris image positioning, feature extraction and image matching, the key findings are as follows: First, for the lack of classic iris location method is proposed based iris image grayscale characteristics of the distribution of improved algorithm. First threshold value is set automatically according to the gradation value of the pupil of the iris image is binarized, and then the image vertical and horizontal directions of the mean gray smoothing processing, to obtain the coordinates of the minimum value to determine a reference point within the pupil, and finally detection operator child to obtain the extreme points of the four cardinal points of the reference point as a boundary point, in order to achieve the iris boundary location. The experimental results show that the algorithm is compared to the classical iris location algorithm, more accurate positioning, faster. Second, the proposed feature extraction method based on the the iris local area extract texture features, to take full advantage of the rich iris texture area, effectively avoid the interference of the eyelids and eyelashes. With directivity in view of the texture features of the iris, using the Haar wavelet packet for feature extraction, to retain only the low-frequency and vertically low-frequency component of the feature vectors, binary coding. Experimental results show that the amount of data encoded to reduce the speed of feature extraction is significantly improved. Finally, for the match distortion caused by the rotation by the eye, using the cyclic shift matching algorithm to solve this problem. The algorithm uses a Hamming distance classifier, shift the iris encoding the circulation Search as the final match based on the minimum distance value. Experimental analysis to determine the best matching algorithm of shift. Above algorithm CASIA V1.0 iris database for experimental sample, in simulation experiments the Matlab7.1 platform. Experimental results show that good comprehensive performance iris recognition method proposed by the paper, the results are satisfactory.

Related Dissertations

  1. Research on Automatic Detection Algorithm for Substructure Distress of Highway Pavement Based on SVM,U418.6
  2. ISAR Imaging Simulation of Space Targets and Target Recognition Based on ISAR Images,TN957.52
  3. Research on Feature Extraction and Classification of Pulse Waveform for Cholecystitis and Nephrotic Syndrome Diagnosis,TP391.41
  4. Application of Q-Learning in the Content-Based Image Retrieval Technology,TP391.41
  5. Research on Transductive Support Vector Machine and Its Application in Image Retrieval,TP391.41
  6. Research on Feature Extraction and Classification of Tongue Shape and Tooth-Marked Tongue in TCM Tongue Diagnosis,TP391.41
  7. Research on Visual Measurement for Spacecraft Rendezvous and Approach,TP391.41
  8. Research on the Image Real-Time Acquisition, Storage and Image Processing System,TP391.41
  9. Feature Extraction, Selection and Combination in Lipreading,TP391.41
  10. Multi-currency Notes Technology Research and Implementation,TP391.41
  11. The Research on Paper Currency Classification Method Based on Harr-Like Feature and Minimal Ball Including Samples,TP391.41
  12. Pavement Distress Recognition Based on Image,TP391.41
  13. Research on Visual Detection and Tracking of Mobile Robots,TP242.62
  14. Research on Fusion Algorithm of Hyper Spectral and High Spatial Resolution Remote Sensing Image,TP751
  15. Research on Standardization and Accuracy of Use on Junior High School Physical Education Teaching Methods,G633.96
  16. An Approach for Identifying a Plant Resistance Gene Based on the Random Forest,Q943
  17. Tobacco Diseases Auto-Recognition Research Based on Image Processing Technology,S435.72
  18. Research on Nondestructive Detection Technology for External Qualities of Papayas Based-on Vision,S667.9
  19. Study on Structral Analysis & Control Method of Generalized Ensemble,N945.1
  20. Research on Development and Production Solution of Furniture Mass Customization by the Advanced Manufacturing Technology,TS664
  21. Research on Identification System of Cashmere and Wool Fiber,TS101.921

CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
© 2012 www.DissertationTopic.Net  Mobile