一种稳健的高效角点特征提取变换
A Robust and Efficient Feature Extract Transform
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摘要: 针对目前基于加速分割的高效角点检测方法存在角点定位不准、对图像亮度变化以及图像边缘敏感等问题,提出了一种鲁棒的高效角点特征提取变换REFET。该算法首先基于人类视觉的颜色恒常性进行图像增强以提高算法对图像亮度变化的鲁棒性,然后根据对角相似性约束对图像进行边缘点粗检测,最后通过一种自适应的检测模板进行角点提取,获取定位准确的角点特征。实验结果表明,本文提出的REFET方法在保证时间效率的同时,提高了特征的定位准确度和对图像亮度变化的鲁棒性,较好地抑制图像边缘点。Abstract: The efficient feature detection is a crucial step for various tasks in computer vision. However, the corner location is not very accurate and some edge pixels have high responses for the kind of corner detector based on the accelerated segment test. Furthermore, this kind of method is sensitive to the change of illumination. This paper presents a robust and efficient feature extraction transform (REFET). The method includes three steps: firstly, the input image is enhanced based on the color constancy of the human vision system. Then, acoarse edge pixel detection method is used to eliminate edge points in the image. Finally, an adaptive mask is proposed to extract corners accurately and efficiently. The experiments demonstrate that the proposed method improves the corner localization accuracy and the robustness for illumination, and the edge points are suppressed in the results.