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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Verikas, A. Malmqvist, K. |
| Copyright Year | 1995 |
| Description | Author affiliation: Image Process. Group, Halmstad Univ., Sweden (Verikas, A.; Malmqvist, K.) |
| Abstract | This paper presents a colour image segmentation method which attains a high segmentation accuracy even when regions of the image that have to be separated are very similar in colour. The proposed method classifies pixels into colour classes. Competitive learning with "conscience" is used to learn reference patterns for the different colour classes. A nearest neighbour classification rule followed by a block of fuzzy post-processing attains a high classification accuracy even for very similar colour classes. A correct classification rate of 97.8% has been achieved when classifying two very similar black colours, namely, the black printed with a black ink and the black printed with a mixture of cyan, magenta and yellow inks. |
| Starting Page | 1713 |
| Ending Page | 1718 |
| File Size | 596175 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780327683 |
| DOI | 10.1109/ICNN.1995.488878 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1995-11-27 |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image segmentation Ink Pixel Printing Image color analysis Neural networks Image processing Quality control Automatic control Vector quantization |
| Content Type | Text |
| Resource Type | Article |
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