摘要：

提出一种基于KL变换和核Fisher判别的车位检测方法，对车位图像进行预处理，将该车位图像投影至已通过KL变换构造出的特征车位子空间中，得到的投影系数即为车位的特征向量，利用核Fisher判别进行车位占用情况的判别。仿真实验采用3种不同的核函数进行核Fisher判别比较，结果表明，采用高斯径向基核函数的车位检测判别方法检测的效果最佳，检测正确率高达97.6%。

关键词: KL变换, 核Fisher判别, 车位检测, 核函数, 径向基函数

Abstract:

This paper presents a kind of parking cell detection method based on KL transform and kernel fisher discriminant. It preprocesses the parking cell images. The parking cell images is projected onto the eigen-parking cell-subspace which is constructed by KL transform, and the coefficients of the projection are the eigen-vector of the parking cell. It makes use of kernel fisher discriminant to determine the occupancy of parking cell. In the experiment, it uses three different kernel functions to compare the results of the fisher discriminant. Experimental results indicate that the parking cell detection method with Radial Basis Funtion(RBF) kernel function is superior to other methods, the correct detection rate reaches as high as 97.6%.

Key words: KL transform, kernel Fisher discriminant, parking cell detection, kernel function, Radial Basis Funtion(RBF)

中图分类号: 

• N945