一种改进的安全带图像特征提取方法的应用

Application of an improved method for extracting safety belt image feature

针对基于支持向量机(SVM)的安全带佩戴视觉检测系统,提出一种改进的安全带图像特征提取方法。通过基于Freeman链码的最小二乘圆弧拟合法识别方向盘边缘圆弧,在安全带边缘特征约束条件下使用快速Hough变换确定备选安全带边缘直线段,进而深入分析方向盘边缘圆弧中点与备选安全带边缘直线段的平面几何关系,并以此为基础构造特征向量,完成对安全带图像特征的提取。实验数据表明,最终获取的特征向量能准确地表征原始图像中的安全带图像特征,适合作为SVM分类器的输入参数。

Aimed at the recognition system of safety belt based on Support-Vector Machine （SVM）, an improved method for extracting safety belt image feature is proposed. Steering wheel edge are is recognized with the method of the least square arc fitting based on Freeman chain code and alternative safety belt edge line segments are determined by means of fast Hough transform within safety belt edge feature constraints. And then feature vectors are constructed by in-depth analysis of plane geometrical relationships among steering wheel edge arc midpoint and alternative safety belt edge line segments. The data of experiments show that the final feature vectors represent the safety belt image feature of original image accurately and are suitable for SVM classifier as input parameters.