基于圆环模板的改进Harris角点检测算法

Improved corner detection algorithm based on circle mask via Harris

Harris算子是经典的角点检测算法,但却存在检测性能依赖高斯窗窗长和阈值的不足,本文对此做出改进。先设定较低阈值,检测出图像中的疑似角点。再构造一个新的圆环模板,通过内外两个圆环上的像素点评估中心像素邻域灰度变化,用构建的新模板遍历每一个疑似角点,滤除虚假角点,得到最终检测结果。本文算法计算内外两个圆环上像素的灰度变化,充分考虑了角点在局部区域灰度变化明显的特征,不涉及微分运算,所以具有较好的鲁棒性。通过一系列实验,新算法在实际应用中明显具备良好的检测性能。

Harris corner detection is a classical algorithm,but the detection result is closely related to selection of the Gaussian window length and the threshold value.Aiming at the problems,an improved algorithm for Harris corner detection is proposed.To begin with,scan the whole image with a lower threshold to extract the suspected corners.And then,a new circle mask is presented to evaluate the gray difference of pixels in the outside circle and the inside circle.The fake corners are eliminated by evaluating every suspected corner with the new circle mask and get the result.The proposed algorithm,avoiding derivative,is stable and robust.The experimental results of a series of images show the effectiveness and feasibility of the proposed method.