CAJ | 학술논문

本文提出了一种基于马尔可夫随机场的运动目标检测算法.针对传统时间分割使用主观固定阁值的缺点,使用马尔可夫随机场模型对差分图像建模,并提出了一种新的模型阶次选择算法,以及一种可以加速收敛过程的随机场迭代算法.采用期望最大算法获取高斯分布参数并检测运动变化区域,利用形态学运算修正时间分割模板;空间分割部分提出了基于人眼视觉特征的改进分水岭算法,有效地解决了过分割问题;最后对时、空间分割结果进行信息融合处理,从而得到完整的运动目标.仿真实验结果证明了本文算法可以有效地分割视频运动目标.
본문제출료일충기우마이가부수궤장적운동목표검측산법.침대전통시간분할사용주관고정각치적결점,사용마이가부수궤장모형대차분도상건모,병제출료일충신적모형계차선택산법,이급일충가이가속수렴과정적수궤장질대산법.채용기망최대산법획취고사분포삼수병검측운동변화구역,이용형태학운산수정시간분할모판;공간분할부분제출료기우인안시각특정적개진분수령산법,유효지해결료과분할문제;최후대시、공간분할결과진행신식융합처리,종이득도완정적운동목표.방진실험결과증명료본문산법가이유효지분할시빈운동목표.
A novel method for detecting moving objects from video sequences is proposed based on Markov random field. In order to overcome the drawback of subjective fixed threshold of traditional temporal segmentation, the difference image is modeled by Markov random field. A novel method for deciding the model size and initial parameters of MRF, and a new iteration method for greatly accelerating the convergence are proposed. Then, the Expectation-Maximization (EM) algorithm is carried out to obtain the Gaussian parameters and temporal moving area is detected. The temporal segmentation is then amended by morphological operations. Considering the lack of traditional spatial segmentation algorithm of watershed, an improved watershed algorithm in accord with the human vision characteristics, which can restrain over-segmentation effectively, is proposed. The temporal and spatial information fusion is fulfilled by ratio operation, and the moving objects are obtained. The emulation experiments demonstrate the validity of the proposed algorithm.