Log-Spiral Keypoint: A Robust Approach toward Image Patch Matching

Abstract EN

Matching of keypoints across image patches forms the basis of computer vision applications, such as object detection, recognition, and tracking in real-world images.

Most of keypoint methods are mainly used to match the high-resolution images, which always utilize an image pyramid for multiscale keypoint detection.

In this paper, we propose a novel keypoint method to improve the matching performance of image patches with the low-resolution and small size.

The location, scale, and orientation of keypoints are directly estimated from an original image patch using a Log-Spiral sampling pattern for keypoint detection without consideration of image pyramid.

A Log-Spiral sampling pattern for keypoint description and two bit-generated functions are designed for generating a binary descriptor.

Extensive experiments show that the proposed method is more effective and robust than existing binary-based methods for image patch matching.