关键词: Gabor变换, BP神经网络, 纹理分析, 皱纹识别, 模式识别

Abstract: For the impact of strong noises such as splashes and pores, human facial wrinkles recognition was severely disrupted, especially for the recognition of facial fine texture. This paper proposed a recognition method based on Gabor filter and BP neural network to recognize facial wrinkles. Firstly, BP neural network was trained to identify the existence of texture by Gabor filtering results and then whether the wrinkles exist or not was judged. One wrinkle sample database was created from a number of face photos with different ages, and the database had been used to train BP neural network. In this paper, wrinkled and non-wrinkled pictures were selected, and then Gabor filter bank was used to calculate their frequency spectrum as the training samples. Then, the trained neural network could be used to recognize human facial wrinkles. A large number of test results show that the algorithm can eliminate or reduce interference of splashes and pores and over 85% recognition accuracy can be got.

Key words: Gabor transformation, Back Propagation (BP) neural network, texture analysis, wrinkles recognition, pattern recognition