Guided Scale Space Radon Transform for linear structures detection

• URL: http://arxiv.org/abs/2311.09103v1
• Date: Wed, 15 Nov 2023 16:50:01 GMT
• Title: Guided Scale Space Radon Transform for linear structures detection
• Authors: Aicha Baya Goumeidane, Djemel Ziou, and Nafaa Nacereddine
• Abstract summary: We propose a method for automatic detection of thick linear structures in gray scale and binary images using the SSRT. This method involves the calculated Hessian orientations of the investigated image while computing its SSRT. As a consequence, the subsequent maxima detection in the SSRT space is done on a modified transform space freed from unwanted parts.
• Score: 1.7205106391379021
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Using integral transforms to the end of lines detection in images with complex background, makes the detection a hard task needing additional processing to manage the detection. As an integral transform, the Scale Space Radon Transform (SSRT) suffers from such drawbacks, even with its great abilities for thick lines detection. In this work, we propose a method to address this issue for automatic detection of thick linear structures in gray scale and binary images using the SSRT, whatever the image background content. This method involves the calculated Hessian orientations of the investigated image while computing its SSRT, in such a way that linear structures are emphasized in the SSRT space. As a consequence, the subsequent maxima detection in the SSRT space is done on a modified transform space freed from unwanted parts and, consequently, from irrelevant peaks that usually drown the peaks representing lines. Besides, highlighting the linear structure in the SSRT space permitting, thus, to efficiently detect lines of different thickness in synthetic and real images, the experiments show also the method robustness against noise and complex background.

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