Multiresolution stroke sketch adaptive representation and neural network processing system for gray-level image recognition

Alexander M. Meystel; Ilya A. Rybak; Sanjay Bhasin

doi:10.1117/12.131607

1 November 1992 Multiresolution stroke sketch adaptive representation and neural network processing system for gray-level image recognition

Alexander M. Meystel, Ilya A. Rybak, Sanjay Bhasin

Author Affiliations +

Proceedings Volume 1826, Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods; (1992) https://doi.org/10.1117/12.131607
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States

Abstract

This paper describes a method for multiresolutional representation of gray-level images as hierarchial sets of strokes characterizing forms of objects with different degrees of generalization depending on the context of the image. This method transforms the original image into a hierarchical graph which allows for efficient coding in order to store, retrieve, and recognize the image. The method which is described is based upon finding the resolution levels for each image which minimizes the computations required. This becomes possible because of the use of a special image representation technique called Multiresolutional Attentional Representation for Recognition, based upon a feature which the authors call a stroke. This feature turns out to be efficient in the process of finding the appropriate system of resolutions and construction of the relational graph. Multiresolutional Attentional Representation for Recognition (MARR) is formed by a multi-layer neural network with recurrent inhibitory connections between neurons, the receptive fields of which are selectively tuned to detect the orientation of local contrasts in parts of the image with appropriate degree of generalization. This method simulates the 'coarse-to-fine' algorithm which an artist usually uses, making at attentional sketch of real images. The method, algorithms, and neural network architecture in this system can be used in many machine-vision systems with AI properties; in particular, robotic vision. We expect that systems with MARR can become a component of intelligent control systems for autonomous robots. Their architectures are mostly multiresolutional and match well with the multiple resolutions of the MARR structure.

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Alexander M. Meystel, Ilya A. Rybak, and Sanjay Bhasin "Multiresolution stroke sketch adaptive representation and neural network processing system for gray-level image recognition", Proc. SPIE 1826, Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods, (1 November 1992); https://doi.org/10.1117/12.131607

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