Abstract: Focusing on object contour extraction technology that had the most significant impact on the process of image analysis, an efficient method was proposed for object contour extraction based on probability distribution. First the foreground object was detected and its hue feature was used to build an object probability model. With this model, the probability distribution image was calculated on the whole image for the object. Finally, the contour was obtained from the probability distribution image directly. After testing the method using 2330 continuous images containing moving object, the results suggest that the method can work efficiently. It takes 20ms to 30ms to process a true color image of 640×480 pixels, and the contours extracted are very clear and accurate.

Key words: image segmentation, probability distribution, contour extraction, object detection, null-parameter density estimate

摘要： 以对图像分析起重要作用的目标轮廓提取技术为重点，研究并提出一种基于概率分布图的目标轮廓快速提取方法，该方法先从视频中检测到前景目标并建立目标概率模型，再根据建立的模型计算目标概率分布图，用该分布图提取出目标轮廓。对2330幅包含运动目标的视频帧进行测试，结果表明，该方法简单有效，处理速度快，提取的轮廓准确、清晰，对目标形变具有很好的鲁棒性。

关键词: 图像分割, 概率分布, 轮廓提取, 目标检测, 无参密度估计