摘要
针对传统Canny边缘检测算法的阈值需要人为设定的缺陷,本文提出了一种新的自适应改进方法。该方法根据梯度直方图信息,提出梯度差分直方图的概念,同时,对图像进行自适应分类处理,使得算法不仅不需要人工设定阈值参数,而且还能有效地避免Canny算法在边缘寻找中的断边和虚假边缘现象。对边缘信息丰富程度不同的灰度图和彩色图像运用该方法寻找边缘的实验结果表明,对于在目标与背景交界处的多数像素梯度幅值较大的图片,该算法具有边缘检测能力强、自适应能力强的优点。
The two thresholds of classical Canny operator need to be set manually, which limits the application of this algorithm. Therefore, many researches about how to choose threshold adaptively are done to solve this problem. Based on the gradient histogram, a method of threshold-adaptable edge detection is proposed. This method is on the basis of gradient histogram difference diagram with adaptive image classification techniques. It not only automatically sets the two thresholds, but also avoids disconnected or false edges in detection. Experiments prove that the method is threshold-adaptive and advantageous for edge detection in color image whose pixels of larger gradient amplitude are mainly located in the edge between the target and background.
出处
《光电工程》
CAS
CSCD
北大核心
2009年第11期106-111,117,共7页
Opto-Electronic Engineering
基金
中国科学院东北振兴科技行动计划重点项目(DBZX-2-017)
吉林省信息产业发展专项资金项目
