纸币图像Gabor特征提取与识别

Paper Currency Image Features Extraction Based on Gabor Filter and Recognition

研究了基于Gabor滤波器组的人民币图像识别方法。针对纸币图像特点,设计了适合于其特征提取的Gabor滤波器组参数,得到了纸币图像多尺度多方向上的纹理特征,然后对纹理图像进行网格划分,并计算网格中像素灰度均值行列投影和,最后采用网格投影特征模板匹配法进行纸币识别。实验表明该法抗干扰能力较强,能够较大提高旧币和污染纸币识别率,并且耗时不长。

The paper currency image recognition method based on Gabor filter set is discussed in this paper. According to the paper currency image features, the suitable parameters of Gabor filter set are selected for paper currency characteristics extraction, the multi-scale and multi-directional texture characteristics of paper currency image are gotten, then the texture im- ages are meshed, and the row and column projection sum of grid pixels＇ average grey are calculated, finally, the template match method based on grid projection characteristics is used for paper currency recognition. Experiments show that this method has strong anti-interference ability, it can raise the recognition rate of old or dirty paper currency greatly, and it costs little time.