CAJ | 학술논문

针对带式输送机在运行过程中输送带易撕裂的背景,根据人眼视觉系统特点和信息论相关理论,提出了一种基于视觉显著性和一维最大熵的输送带撕裂故障检测算法.首先在频域提取图像的显著性区域,然后计算显著图的最大信息熵,进而分割图像.实验结果表明,该方法具有较强的稳定性和适应性.
침대대식수송궤재운행과정중수송대역시렬적배경,근거인안시각계통특점화신식론상관이론,제출료일충기우시각현저성화일유최대적적수송대시렬고장검측산법.수선재빈역제취도상적현저성구역,연후계산현저도적최대신식적,진이분할도상.실험결과표명,해방법구유교강적은정성화괄응성.
Under the background that conveyor belts are prone to rips in operation, According to the characteristics of human visual system and information theory, an algorithm for detecting rips in conveyor belts based on visual saliency and maximal entropy is proposed. Regions of interest are firstly extracted in frequency domain, and then a threshold is obtained through calculating the maximal entropy of saliency map to segment the grayscale image. Experiments show that the algorithm is stable and adaptable.