Paper
10 October 1994 Color scene representation for model-based matching
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Abstract
This paper describes the relational graph description of natural color scenes and the model- based matching using relational distance measurement. The uniformly colored object areas and the textured surfaces of natural scenes are extracted using color clustering and linear discriminant. The extracted object regions are refined in the spatial plane to eliminate the fine grain segmentation results. The refined segments and regions are then represented using an adjacency relation graph. Scene model is characterized by means of 3-D to 2-D constraints and adjacency relations. The relational-distance measure is used for matching the relational graphs of the input scene and the respective image. Experiments are conducted on imperfect color images of outdoor scenes involving complex shaped objects and irregular textures. The algorithm has produced relatively simple relational graph representation of the input scenes and accurate relational-distance-based matching results.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mehmet Celenk "Color scene representation for model-based matching", Proc. SPIE 2353, Intelligent Robots and Computer Vision XIII: Algorithms and Computer Vision, (10 October 1994); https://doi.org/10.1117/12.188927
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Cited by 1 scholarly publication.
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KEYWORDS
Image segmentation

Roads

Image processing

Distance measurement

Image processing algorithms and systems

Model-based design

Image analysis

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