基于灰度直方图的运动目标特征检测算法

为提高运动目标的检测效果和指导性，提出一种基于灰度直方图分析的运动目标特征检测算法。采用视觉成像技术进行运动目标图像采集和视觉特征分析，提取运动目标的动态视觉特征量。根据运动目标边缘差分变换和空间位置关系进行运动图像的特征分离，提取运动目标图像的边缘轮廓特征量。采用统计形状模型进行运动目标图像的二值化分离，构建运动目标图像的灰度直方图。根据灰度直方图中的统计信息进行目标特征检测和动态特征提取，实现运动目标图像的视觉检测和动态识别，有效提取运动目标的关键特征，实现目标特征检测。仿真结果表明，采用该方法进行运动目标图像的特征检测性能较好，对运动目标的动态识别能力较强。

Feature Detection Algorithm for Moving Objects Based on Gray Histogram

In order to improve the detection effect and guidance of moving targets, a feature detection algorithm based on gray histogram analysis is proposed. The moving object image is collected and the visual feature is analyzed by using the visual imaging technology, and the dynamic visual feature quantity of the moving object is extracted. The feature separation of the moving image is carried out according to the moving object edge differential transform and the spatial position relation, and the edge contour feature of moving object image is extracted. The binary separation of moving object image is carried out by using statistical shape model, and the gray histogram of moving object image is constructed. According to the statistical information of gray histogram, the object feature detection and dynamic feature extraction are carried out to realize the visual detection and dynamic recognition of moving target image. The key features of moving object are extracted effectively and the target feature detection is realized. The simulation results show that the proposed method has better performance in feature detection of moving target images and dynamic recognition ability for moving targets.