摘要
针对传统Sobel边缘检测算法需要人为指定阈值而且检测出的边缘较宽等问题,提出一种自适应阈值和非极大值抑制相结合的边缘检测算法。引入中值滤波的思想生成自适应动态阈值,将该值作为二值化处理的阈值,并采用非极大值抑制的方法细化梯度图像,同时通过增加梯度检测方向提高了算法对复杂纹理的识别能力。将改进后的算法在FPGA平台上实现,实验验证了其有效性。
In order to solve the problem of the traditional Sobel algorithm which needs a given threshold and produces wideedge, an improved edge detection algorithm which combines the adaptive threshold and the non-maximum suppression was pro-posed. The median filtering was introduced to generate adaptive dynamic threshold for binarization processing. The non-maximumsuppression method was applied to refine gradient image while the detection direction was expanded to improve the identificationability for complex textures. The improved Sobel edge detection algorithm was realized based on FPGA and verified by the experi-mental results to be effective.
出处
《仪表技术与传感器》
CSCD
北大核心
2018年第2期101-104,108,共5页
Instrument Technique and Sensor
基金
国家自然科学基金项目(61201391)