Color scene recognition using relational distance measurement

Mehmet Celenk

doi:10.1117/12.233239

27 February 1996 Color scene recognition using relational distance measurement

Mehmet Celenk

Proceedings Volume 2727, Visual Communications and Image Processing '96; (1996) https://doi.org/10.1117/12.233239
Event: Visual Communications and Image Processing '96, 1996, Orlando, FL, United States

Abstract

In this paper, we present a method for the recognition of color images of outdoor scenes using the relational graph description and distance measurement. Color scenes of interest are modeled by considering 3-D to 2-D constraints, regions' color properties, and regions' adjacency relations. The scene models are stored in a database system in region adjacency graph format. Each node of the graph represents an object or surface in the scene and includes object's or surfaces color as its unary property. Edges of the graph correspond to the binary adjacency relations between the objects or surfaces in accordance with the 3-D to 2-D mapping constraints. For the recognition of a color image of unknown origin, the uniformly colored object areas in the image are extracted using color clustering and linear discriminant. The textured surfaces are then segmented by the Julesz conjecture. The extracted object regions are refined in the spatial plane to eliminate the fine grain segmentation results. The extracted regions are used as the nodes of the image region adjacency graph. The nodes are assigned the region's color information as their unary properties. If two object regions share a common boundary, they are considered adjacent and their respective nodes are connected by an edge. A relational homomorphism (i.e., mapping function) from the image graph to the scene graph is determined considering the unary properties and binary relations in their respective graph representations. The relational-distance measure is used for matching the relational graphs of the input scenes and the respective images. The scene graph with the minimum structural error is selected as the best match for the image being processed.

Citation Download Citation

Mehmet Celenk "Color scene recognition using relational distance measurement", Proc. SPIE 2727, Visual Communications and Image Processing '96, (27 February 1996); https://doi.org/10.1117/12.233239

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KEYWORDS

Image segmentation

Image processing

Distance measurement

3D modeling

Binary data

Roads

Data modeling

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