A Novel Image Enhancement Method for SIFT Feature Extraction of Low Resolution Palmprint Images

作者：Liu Di^*; Sun Dongmei; Qiu Zhengding

来源：Chinese Journal of Electronics, 2011, 20(1): 111-113.

• Local gray entropy
• Scale invariance feature transformation (SIFT) keypoints
• Palmprint recognition

When using the existing methods to carry out the enhancement of the low resolution palmprint images, Scale invariance feature transformation (SIFT) keypoints used for identification can not be efficiently yield. To solve this problem, this paper proposes a promising local entropy-based Unsharpen Masking algorithm for SIFT feature extraction of the images described above. This method can adaptively improve the contrast of the images to extract SIFT features from palmprint while it does not distort the characteristic of the palmprint texture. The scheme introduces local entropy of the images as the enhancement coefficients. The experimental results show the proposed method can successfully extracts as many as possible SIFT keypoints from the enhanced palmprint images, in contrast to the failure by traditional Unsharp Masking-based schemes.

• 出版日期2011-1
• 单位北京交通大学