奇异值方法用于汽车车型识别

Car Shape Recognition Based on Matrix Singular Value

图象灰度矩阵奇异值是图象的代数特征 ,已有文献把奇异值方法用于图象识别 ,针对常用的图象识别方法不能对外形区别不大的汽车及受到干扰的汽车进行识别的问题 ,把图象矩阵奇异值方法用到汽车车型识别的研究中 .由于光照强度的影响 ,使处于同一场景的图象往往具有不同的灰度 ,且将影响奇异值方法的使用 ,所以引入了灰度一致因子来校正图象灰度 .并用该方法对一些汽车图象进行了实验分析 ,取得了比较好的结果 .最后 ,对这一方法进行了一些定性与定量分析 ,并提出了理论上需进一步探讨的问题 .

Type and shape of the car is coherent, one type of the car possess the one and only shape. Based on this fact, instead of recognition of the type of the car, recognition of the shape of the car is discussed detailed in this paper. Considering that a few methods proposed in the correlate paper are not accurate and those methods are lack of gracefulness, matrix singular value method is used in car shape recognition in this paper. As one of algebraic characters of matrix, singular value is reported to be used in image recognition, such as human face recognition, but the report about the method used in recognition of the vehicle shape has not been accessible. In order to standardize the different weight of the images in the same sites owing to different light, gray level rectified factor is put forward. At last, quantitative and qualitative analysis about the methods is proposed.