Research Of The Feature Fution Of The Knuckle-print Identification Method

With the rapid development of modern science and technology, the concept of legalsystem gradually deepens, the demand for personal identification is more and more extensive,because of the drawbacks of the traditional identification methods, biometric technology wasborn, and is now widely used in various fields. Knuckle-print is an emerging biometric; it hasspecial features in addition to other characteristics such as the stability and distinguishcharacteristics. In this paper, the Knuckle-print was chosen for Biometric identification, andstudy the feature extraction algorithm in the identification process.Feature extraction is the key to the whole process of the Knuckle-print recognition, howto extract features effectively is becoming one of the important attentions. Because of certainlimitations of single biological characteristics, information fusion is introduced to thebiological characteristics identification. This paper put forward feature extraction algorithmand character fusion algorithm, the main research work are as follows:(1)Feature extraction of the Knuckle-print. We use the typical method of featureextraction which is the Gabor filter, PCA to extract features respectively, and propose amethod which is based on the local binary mode to extract the Knuckle-print feature.(2) Put forward algorithm based on Gabor and PCA for the feature extraction of theKnuckle-print. The experimental results show that the recognition rate of the method is betterthan used Gabor and PCA method alone respectively.(3) This paper puts forward method of the characteristics fusion for the Knuckle-printrecognition due to the limitations of the single feature identification.The proposed algorithms can effectively implement knuckle-print identification. It isshown by experiments which proceed in our own building image data and the data providedby Information Institute of Beijing Jiaotong University.