CAJ | 학술논문

在智能视频监控中,运动目标的准确提取至关重要. 现有的运动目标检测算法虽然很多,但是阴影去除效果都不甚理想,因此提出了一种基于RGB和HSI颜色空间的阴影消除改进算法. 该算法在分析视频中像素点被阴影覆盖和未被阴影覆盖时色调的近似一致性和亮度值成线性关系的基础上,利用2个颜色空间中组成颜色的各分量值在该颜色中所占的比例和亮度的相对变化率,实现运动目标的阴影消除. 实验表明,该算法去除阴影的效果优于采用( r, g, I)颜色空间阴影去除算法,且能有效弥补运动目标孔洞的现象,是对运动目标检测算法的补充.
재지능시빈감공중,운동목표적준학제취지관중요. 현유적운동목표검측산법수연흔다,단시음영거제효과도불심이상,인차제출료일충기우RGB화HSI안색공간적음영소제개진산법. 해산법재분석시빈중상소점피음영복개화미피음영복개시색조적근사일치성화량도치성선성관계적기출상,이용2개안색공간중조성안색적각분량치재해안색중소점적비례화량도적상대변화솔,실현운동목표적음영소제. 실험표명,해산법거제음영적효과우우채용( r, g, I)안색공간음영거제산법,차능유효미보운동목표공동적현상,시대운동목표검측산법적보충.
It is critical to exactly extract moving targets in intelligent video surveillance. There are many moving tar-get detection algorithms, but for all the effects of shadow elimination are not ideal. In order to remove the shadow, an improved shadow removal algorithm based on RGB and HSI color spaces is presented. The analysis of the pixels in videoes shows that the hue is approximately consistent before and after the pixels are shaded, and there exists a linear relation between this approximate consistency and the value of luminance. On this basis, by utilizing the pro-portion of each color component in the color spaces and the relative change rates of brightness, the shadow of a moving object can be removed. The experimental results show that the shadow removal effect of this algorithm is bet-ter than that of the algorithm with ( r, g, I) color space. In addition, it can also cope with holes in moving targets and is a supplement to the moving object detection algorithm.