计算机科学
人工智能
阈值
像素
计算机视觉
边缘检测
特征提取
绘图
高斯滤波器
Canny边缘检测器
GSM演进的增强数据速率
模式识别(心理学)
斑点检测
图像渐变
高斯分布
直线(几何图形)
图像处理
图像(数学)
计算机图形学(图像)
数学
物理
量子力学
几何学
作者
Haozhe Chen,Chi Zhang,Qiang Yu,Chuanbin Gong
标识
DOI:10.1109/isctech58360.2022.00127
摘要
Edge features are an important feature in our study of graphics, so accurate edge detection is of great importance for image recognition, processing of images and applications in areas such as video surveillance. While the recognition accuracy of our research images often only stays at the pixel level, there is still a lot of room for exploring the sub-pixel level edge extraction of images. In this paper, we compare the extraction principles of various mainstream operators and finally apply the Devernay algorithm based on the Canny operator. Using Gaussian filtering and Gaussian bilateral filtering for image pre-processing, combined with a reasonable threshold setting for the distance between the line segment set and the next detected line segment set and the double thresholding method, completes the sub-pixel level edge extraction for images in various environments, which improves the extraction clarity by more than 40%.
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