Multi scale multi structuring element top-hat transform for linear feature detection

• Main Authors: Xiangzhi Bai, Fugen Zhou, Bindang Xue
• Format: Conference Proceeding
• Language: English
• Subjects: Algorithm design and analysis; Detectors; Feature extraction; Image edge detection; Noise; Pattern recognition; Transforms
• ISSN: 1051-4651; 2831-7475

To efficiently detect all the possible linear features, a multi scale multi structuring element top-hat transform based algorithm is proposed in this paper. The algorithm is divided into two parts: the multi scale multi structuring element top-hat transform and postprocessing. In the multi scale multi structuring element top-hat transform, multi scales of multi structuring elements with increasing sizes are used by the top-hat transform to extract the useful information of linear features. In the post processing, the detected linear feature regions are binarized, firstly. Then, the small noise regions are removed. After that, the final linear feature regions are thinned to form the final binary detected linear features. Experimental results show that, the proposed algorithm could efficiently detect all the possible linear features of different types of images and could be widely used for linear feature detection in different applications.