Linear Structures Identification in Images Using Scale Space Radon Transform and Multiscale Image Hessian.

In this paper we propose a stand-alone method to identify lines of different thickness in an image exploiting the scale Space Radon Transform (SSRT) combined to multiscale image Hessian. The proposed approach does not need any prior knowledge about the image content, neither make any assumption about the image to make a decision of the presence or not of a line. This work which consists in seeking information about possible presence of linear structures in an image and exploiting this information while constructing the SSRT space, limits the SSRT computation around precomputed zones. The latter are obtained by multiscale image Hessian. As a consequence, the subsequent maxima detection is done on a restricted transform space freed from unwanted peaks that usually drown the peaks representing lines. Tests done on synthetic and real images have shown that our method highlight the useful maxima of the SSRT permitting to improve SSRT detection of lines of different thickness in an image, while preserving computation time.