Digital Straight Segment Filter for Geometric Description

International audienceIn this paper, an algorithmic scheme is proposed to estimate different local characteristics of image structures using discrete geometry tools. The arithmetic properties of Digital Straight Lines and their link with the Farey sequences allow the introduction of a new directional filter. In an incremental process, it provides local geometric information at each point in an image, such as the length, orientation and thickness of the longest Digital Straight Segment passing through that point. Experiments on binary and grayscale images are proposed and show the interest of this tool. Comparisons to a well-known morphological filter for grayscale images are also presented

Image Feature Information Extraction for Interest Point Detection: A Comprehensive Review

Interest point detection is one of the most fundamental and critical problems in computer vision and image processing. In this paper, we carry out a comprehensive review on image feature information (IFI) extraction techniques for interest point detection. To systematically introduce how the existing interest point detection methods extract IFI from an input image, we propose a taxonomy of the IFI extraction techniques for interest point detection. According to this taxonomy, we discuss different types of IFI extraction techniques for interest point detection. Furthermore, we identify the main unresolved issues related to the existing IFI extraction techniques for interest point detection and any interest point detection methods that have not been discussed before. The existing popular datasets and evaluation standards are provided and the performances for eighteen state-of-the-art approaches are evaluated and discussed. Moreover, future research directions on IFI extraction techniques for interest point detection are elaborated

Dominant point detection based on discrete curve structure and applications

International audienceIn this paper, we investigate the problem of dominant point detection on digital curves which consists in nding points with local maximum curvature. Thanks to previous studies of the decomposition of curves into sequence of discrete structures [1, 2, 3], namely maximal blurred segments of width ν [4], an initial algorithm has been proposed in [5] to detect dominant points. However, an heuristic strategy is used to identify the dominant points. We now propose a modied algorithm without heuristics but a simple measure of angle. In addition, two applications are as well presented: (1) polygonal simplication to reduce the number of detected dominant points by associating a weight to each of them, and (2) classication using the polygon issued from the reduced dominant points. The experimental results demonstrate the eciency and robustness of the proposed method