CAJ | 학술논문

针对木粉显微图像边缘复杂、细节模糊等问题，提出一种基于HSV空间目标提取和改进数学形态学多尺度算子的边缘检测算法。基于HSV空间提取目标，排除背景噪声干扰；通过最佳方向检测改进传统多尺度形态学检测算子，避免了多方向检测的权重选择，以此获得较好的木粉边缘。实验结果表明：形态学检测算子优于传统canny检测算子；改进的形态学多尺度检测算子不但取得了较好的边缘检测效果，而且提高了边缘检测精度和定位能力。
침대목분현미도상변연복잡、세절모호등문제，제출일충기우HSV공간목표제취화개진수학형태학다척도산자적변연검측산법。기우HSV공간제취목표，배제배경조성간우；통과최가방향검측개진전통다척도형태학검측산자，피면료다방향검측적권중선택，이차획득교호적목분변연。실험결과표명：형태학검측산자우우전통canny검측산자；개진적형태학다척도검측산자불단취득료교호적변연검측효과，이차제고료변연검측정도화정위능력。
Since a wood-flour microscopic image usually contains complex edge, fuzzy boundary and so on, an edge detec-tion method based on object extraction and modified mathematic morphological multi-scale operator in the color space of HSV is proposed. This method extracts objects for avoiding background noise interference, and gains better wood-flour edge based on traditional multi-scale morphological operator combined with the best direction detection without the weight choice of the multi-direction detection. The experimental results demonstrate that morphological operator is better than traditional canny operator. The modified operator proposed contributes to a distinct edge detection result, improving detection accuracy as well as the capability of edge positioning.