摘要
在利用Canny算法将空间边缘信息结合到基于变化的分割技术的基础上,提出在预处理阶段对视频序列的灰度图进行局部对比度增强处理,以增加前景物体与背景对比度的观点,解决了许多视频分割算法都存在的对比度较低带来分割困难的问题,并通过设计滤波器来滤除对比度增强之后引入的少量噪声;然后针对复杂背景的情况,利用随机信号的统计特性累计得到算法所需的背景,实现背景信息的自动获取;最后利用背景累积过程中分类讨论的观点,解决了物体停止运动时间较长时的分割丢失问题.通过几个典型的MPEG-4测试序列进行实验,实验结果表明,该算法可以有效地将运动物体从视频序列中自动地分割出来.
On the base of combining change-detection-based segmentation approach and spatial edge information by Canny edge detection, an algorithm is proposed that a local contrast enhancement is applied to improve the contrast between the foreground object and background in the pre-processing stage, so that the contrast between the foreground and background is enhanced, and the problem caused by low contrast is solved. A filter was designed to remove a modicum of noise caused by contrast enhancement processing. Then for the complex background, the algorithm utilizes probability-based classification to accumulate the background information, which is needed by the original segmentation algorithm, and consequently realizes the capturing of the background information automatically; Finally, the paper proposed that three situations should be discussed in the process of accumulating background information, and the problem of part loss of the segment due to the object being still for a long time. The proposed algorithm is evaluated on several MPEG-4 test sequences and produces promising results.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2006年第3期230-234,共5页
Transactions of Beijing Institute of Technology
基金
中国科学院海外杰出学者基金资助项目(E09JJ02)
关键词
视频分割
CANNY边缘检测
对比度增强
随机信号的检测
video segmentation
Canny edge detection
contrast strengthen
probability-based classification
