CAJ | 학술논문

针对采集图像中物体附近可能会形成阴影而造成干扰的问题，提出一种利用形态学修复方法和经验模态分解(empirical mode decomposition，EMD)技术实现阴影去除与目标图像的准确提取的方法。采用背景差分和二值图像形态学修复方法检测出含有目标及其阴影的区域，利用经验模态分解方法对该检测区域的灰度直方图曲线进行处理，获取灰度模式变化信息，将搜寻到关于目标及其阴影分割的双阈值水平，结合到形态学修复以实现阴影区域的去除，并以汽车及行人图像处理的实验进行验证。实验结果证明：图像中的目标阴影得到有效去除，该方法具有良好的适应性，能够获得准确的目标检测效果。
침대채집도상중물체부근가능회형성음영이조성간우적문제，제출일충이용형태학수복방법화경험모태분해(empirical mode decomposition，EMD)기술실현음영거제여목표도상적준학제취적방법。채용배경차분화이치도상형태학수복방법검측출함유목표급기음영적구역，이용경험모태분해방법대해검측구역적회도직방도곡선진행처리，획취회도모식변화신식，장수심도관우목표급기음영분할적쌍역치수평，결합도형태학수복이실현음영구역적거제，병이기차급행인도상처리적실험진행험증。실험결과증명：도상중적목표음영득도유효거제，해방법구유량호적괄응성，능구획득준학적목표검측효과。
A fusion analysis method was explored for the shadow interference problem near the objects in the image. The mathematical morphology and empirical mode decomposition (EMD) were adopted to achieve the shadow removal and accurate extraction of the target image. The background subtraction and mathematical morphology were applied for the binary image, and to detect the region which contained the target and its shadow. Then, the empirical mode decomposition method was utilized to acquire the grayscale mode information from the gray histogram curve of detection region. Hereafter, the dual-threshold level could be found to distinguish the target and its shadow, the morphological technology was combined to repair the binary image. Finally, the shadow was removed. The images of car and pedestrian was tested to prove the result. The experimental results showed that the shadow of target in images could be removed effectively. The proposed method is well adaptable, and it can achieve the accurate target detection purpose.