Ridge Detection by Image Filtering Techniques: A Review and an Objective Analysis - IMT Mines Alès Accéder directement au contenu
Article Dans Une Revue Распознавание образов и анализ изображен / Pattern Recognition and Image Analysis: Advances in Mathematical Theory and Applications Année : 2021

Ridge Detection by Image Filtering Techniques: A Review and an Objective Analysis

Résumé

Ridges (resp., valley) are the useful geometric features due to their wide varieties of applications, mainly in image analysis problems such as object detection, image segmentation, scene understanding, etc. Many characterizations have contributed to formalize the ridge notion. The signification of each characterization rely however on its actual application. The objective analysis of ridge characterized as thin and complex image structure is thus essentially important, for choosing which parameter’s values correspond to the suitable configuration to obtain accurate results and optimal performance. In this article an extensive analysis followed by a supervised and objective comparison of different filtering-based ridge detection techniques is led. Furthermore, the optimal parameter configuration of each filtering techniques aimed for image salient feature analysis tool have been objectively investigated, where each chosen filter’s parameters corresponds to the width of the desired ridge or valley. At last, the comparative evaluations and analysis results are reported on both synthetic images, distorted with various types of noises and real images.
Fichier principal
Vignette du fichier
ridge-detection-by-image-filtering.pdf (3.45 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03353145 , version 1 (24-05-2022)

Identifiants

Citer

Ghulam-Sakhi Shokouh, Baptiste Magnier, Binbin Xu, Philippe Montesinos. Ridge Detection by Image Filtering Techniques: A Review and an Objective Analysis: review. Распознавание образов и анализ изображен / Pattern Recognition and Image Analysis: Advances in Mathematical Theory and Applications, 2021, 31 (3), pp.551-570. ⟨10.1134/S1054661821030226⟩. ⟨hal-03353145⟩
126 Consultations
887 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More