A Neural Network Technique for Feature Extraction to Improve Object Recognition

Michael C. Stinson

doi:10.1117/12.969755

1 March 1990 A Neural Network Technique for Feature Extraction to Improve Object Recognition

Michael C. Stinson

Proceedings Volume 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques; (1990) https://doi.org/10.1117/12.969755
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States

Abstract

This paper reports on an object recognition system that combines a neural network global approach with assistance from local features. The Relevant Feature Technique uses a global classifier to determine a characteristic class and uses the local relevant features of that class to improve the recognition of the visual object. Predominantly local features are difficult to utilize in a neural network environment because they are local, and may not be considered significant to the globally sensitive neural network. In the technique shown here, locally relevant features are used to influence and constrain global recognition process.

Citation Download Citation

Michael C. Stinson "A Neural Network Technique for Feature Extraction to Improve Object Recognition", Proc. SPIE 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques, (1 March 1990); https://doi.org/10.1117/12.969755

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