Fusion of self-organizing network and response analysis in object recognition with the hybrid evolutionary algorithm

Igor V. Maslov

doi:10.1117/12.526167

28 May 2004 Fusion of self-organizing network and response analysis in object recognition with the hybrid evolutionary algorithm

Igor V. Maslov

Author Affiliations +

Proceedings Volume 5298, Image Processing: Algorithms and Systems III; (2004) https://doi.org/10.1117/12.526167
Event: Electronic Imaging 2004, 2004, San Jose, California, United States

Abstract

The paper introduces the approach to the 2D automated content-based object recognition utilizing the hybrid evolutionary algorithm (HEA), self-organizing network (SON), and response analysis. When the object is distorted and spatially misregistered, the recognition system has to solve a nonlinear global search problem, i.e. find simultaneously the global positioning of the object and the parameters of its local distortion. The task is accomplished with the HEA using the operators of selection and recombination for the global search, and the accelerated Downhill simplex method for the local search. The algorithm minimizes the fitness formulated as the normalized least squared difference between the images of the scene and the object, and utilizes image local response. The response adequately captures the dynamics of the image transformation, which makes it particularly well suited for the evolutionary search. The response matrix of the object is evaluated and presented to a SON. The weights are computed during the iterative learning process. The resulting adaptive response map serves as the footprint of the object. The evolutionary procedure identifies potential matches for the object based on the response matrix. The local refining procedure uses the response map to accelerate local search in the vicinity of the potential optimal solution.

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Igor V. Maslov "Fusion of self-organizing network and response analysis in object recognition with the hybrid evolutionary algorithm", Proc. SPIE 5298, Image Processing: Algorithms and Systems III, (28 May 2004); https://doi.org/10.1117/12.526167

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KEYWORDS

Evolutionary algorithms

Image segmentation

Object recognition

Dysprosium

Image analysis

Network security

Distortion

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