Abstract: The palm ridge characteristic is the most effective feature of palmprint.At the acquisition time,palm will produce problems of inconsistent scale,rotation,translation and so on,which make accurately extracting and describing ridge feature become a major difficulty in palmprint recognition.To solve these problems,a novel palmprint recognition algorithm based on a fusion of horizontal gradient orientation and local information intensity(referred FHOG-LII) was proposed.First,we used the mean filter with different templates to remove fine,irregular and unstable characteristics of palm ridge,and used horizontal gradient operator to handle the processed image the processed image and then made image binarization.Secondly,we used the thoughts of blocks to calculate information intensity of palm ridge and made it as feature vector.At last,we used the chi-square distance to match them.Experimental results on PolyU palmprint database show that the proposed method can obtain state-of-the-art recognition accuracy(99.89%).Compared with some traditional methods,the recognition rate improves significantly,indicating the effectiveness of the proposed algorithm.

Key words: Palmprint recognition,Binarization,Mean filter,Horizontal gradient operator,Local information intensity,Chi-square distance