Title

Image Recognition Systems Based on Random Local Descriptors

Abstract

Two image recognition systems based on Random Local Descriptors are described. Random Local Descriptors play the role of features that have to be extracted from the image. The advantage of this type of features is a possibility to create sufficiently general description of the image. This approach was tested in different image recognition tasks: handwritten digit recognition, face recognition, metal surface texture recognition and micro work piece shape recognition. The best result for handwritten digit recognition on the MNIST database is the error rate of 0.37% and for face recognition on the ORL database is the error rate of 0.1%. The results for texture and micro work piece shape recognition are also promising.

Meeting Name

2006 International Joint Conference on Neural Networks, IJCNN '06 (2006: Jul. 16-21, Vancouver, British Columbia, Canada)

Department(s)

Electrical and Computer Engineering

International Standard Book Number (ISBN)

9780780394902

International Standard Serial Number (ISSN)

1098-7576

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2006 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.


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