Rotation invariant feature lines transform for image matching
Zhang Ye, Hongsong Qu · Journal of Electronic Imaging · 2014
Image matching has been one of the most fundamental issues in computer vision over the decades. We propose a method based on utilizing feature lines in order to achieve more robust image matching, which includes feature line detection, feature vector description and matching, and the devised rotation invariant feature line transform. The feature vectors have the properties of rotation and scaling invariance. Experimental results demonstrate the effectiveness and efficiency of the proposed method. Compared with the famous powerful algorithm scale invariant feature transform, the proposed method is more insensitive to noise, and the selected distinctive locations of features are more disperse. For a certain sequence of images, which contain strong lines, the proposed method is more efficient. Using the feature lines obtained by our method, it is possible to match two scene images with different rotation angles, scales, and light distortion, and the steps of matching are simpler.