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- From: rpatil@nmsu.edu (Raj Patil)
- Newsgroups: comp.graphics.visualization
- Subject: Object Classification...
- Message-ID: <RPATIL.92Jul27134454@pylos.nmsu.edu>
- Date: 27 Jul 92 20:44:54 GMT
- Sender: usenet@nmsu.edu
- Distribution: comp.graphics.visualization
- Organization: Computing Research Lab
- Lines: 29
-
-
- Hi:
-
- I am faced with following problem to be solved using image processing
- techniques:
-
- We are trying to classify different non-lint particles in a cotton sample
- using imaging techniques.
-
- Cotton sample after ginning contains different kind of trash material on the
- basic of which cotton is graded for it quality. The trash (non-lint particles)
- are of type pieces of leaf, bark, sticks, pepper (fine pieces of leaf),
- cotton seed coat fragments, etc. We are looking at different features
- of these particles, area, perimeter, shape factor, eccentricity, moments etc.
- Using these features we have achieved fairly good classification. We also
- used clustering approaches, Neural nets etc.
-
- Those who have seen some of these non-lint particles, is these anything else
- that we need to consider as feature, in order to get a better
- classification ? Like most of real life problems, one major problem is
- of overlapping clusters of these trash types and increasing feature
- space may improve the classification.
-
- Any suggestions and ideas are appreciated.
-
- Regards
-
- raj
- USDA, ARS
-