A procedure of multispectral analysis was developed to classify a two category image. The procedure utilized pattern recognition and feature extraction techniques. Images were acquired using a computer vision system with a series of interference filters to limit the wavelength band of the images. The procedure developed for multispectral analysis is: (1) Filter selection and image acquisition. (2) Pattern recognition. (3) Bayes minimum error rate classification. (4) Feature extraction by Fisher transformation or by Hotelling transformation. The analytical procedure was programmed in Microsoft C computer language and implemented on an IBM AT computer. The system was tested by identifying an apple against a Formica background. The classified images and histograms indicated that the separation was possible.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/277229 |
| Date | January 1989 |
| Creators | Yan, Bolin, 1954- |
| Contributors | Jondan, K. A. |
| Publisher | The University of Arizona. |
| Source Sets | University of Arizona |
| Language | en_US |
| Detected Language | English |
| Type | text, Thesis-Reproduction (electronic) |
| Rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. |
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