摘要
针对户外监视应用背景,提出了彩色图像差值模型、自适应阈值分割算法、图像形态学噪声滤除方法,实现了户外场景中运动目标的有效检测;对分割后的目标,提取不变矩特征,然后利用人工神经网络实现了运动目标的快速识别。实验结果验证了上述方法的有效性。
This paper first presents an efficient moving object detection method for outdoor surveillance environments. The presented method consists of a color image difference model, an adaptive thresholding method, and an image morphology filtering method. Moreover, by extracting shape invariant moment characteristics of object region, this paper also presents a BP neural network based object recognition method. Experimental results demonstrate that the proposed approach can detect and identify moving objects effectively for outdoor surveillance environments.
出处
《计算机工程》
CAS
CSCD
北大核心
2004年第16期143-145,共3页
Computer Engineering
关键词
运动目标检测
视频监视系统
图像分割
人工神经网络
图像形态学
Moving object detecting and recognition
Video monitoring system
Image segmentation
BP neural network
Image morphology
