Computer Vision in Control Systems-3 pp 119-147 | Cite as
Extraction and Selection of Objects in Digital Images by the Use of Straight Edges Segments
Abstract
New method for finding geometric structures in digital gray-level images is proposed. The method is based on grouping straight line segments, which correspond to the edges of the object. It includes extraction of straight line segments by oriented filtering of gradient image and gives the ordered list of segments with the endpoints’ coordinates for each segment. Adaptive algorithm for straight edge segments extraction is developed that uses angle adjustment of oriented filter in order to extract the line corresponding to the real edges accurately. This algorithm permits the extraction and localization of artificial objects with the rectangular or polygonal shape in digital images. Perceptual grouping approach is applied to extracted segments in order to obtain the simple and complex structures of lines using their crossings. Proposed approach uses the points of intersection of ordered segments as the main property of object structure and also takes into account some specific properties of grouped lines, such as the anti-parallelism, proximity, and adjacency. At the first step, the simple structures are obtained by lines grouping taking into consideration all crossing lines or only part of them. At the second step, these simple structures are joined allowing for restrictions. Initial image is transformed to a collection of closed rectangular or polygonal structures with their locations and orientations. Structures obtained by this method represent an intermediate-level description of interesting objects, which have polygonal view (buildings, parts of roads, bridges, and some natural places of landscape). Application with real aerial and satellite images shows a good ability to separate and extract the specific objects like buildings and other line-segment-rich structures.
Keywords
Line-segment detector Local descriptors Geometric primitives Edge-based feature detector Perceptual contour grouping Object recognition Content-based image retrieval Building and road extraction Feature-based image matchingNotes
Acknowledgements
Author thanks to Prof. Rudolf Germer from TU Berlin for collaboration, Dr. J. Wernicke from EMT (Penzberg) for picture material and HTW Berlin and DAAD for support of the work.
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