Conference proceeding
Multiresolution stroke sketch adaptive representation and neural network processing system for gray-level image recognition
Proceedings of SPIE, v 1826(1), pp 261-278
01 Nov 1992
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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Details
- Title
- Multiresolution stroke sketch adaptive representation and neural network processing system for gray-level image recognition
- Creators
- Alexander M Meystel - Drexel UniversityIlya A Rybak - University of PennsylvaniaSanjay Bhasin - Drexel University
- Publication Details
- Proceedings of SPIE, v 1826(1), pp 261-278
- Conference
- Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods, 11th
- Publisher
- Society of Photo-Optical Instrumentation Engineers (SPIE)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Neurobiology and Anatomy
- Web of Science ID
- WOS:A1992BX17F00026
- Other Identifier
- 991019231646004721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Engineering, Electrical & Electronic
- Neurosciences