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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Musa, Z. Abdul Kadir, T.A. Abu Bakar, R. |
| Copyright Year | 2007 |
| Description | Author affiliation: Univ. Malaysia Pahang, Kuantan (Musa, Z.; Abdul Kadir, T.A.; Abu Bakar, R.) |
| Abstract | Nowadays in the textile industry are still used a human naked eyes to detect any kinds of defect on textile webs. The problems occurred when a human has their own limitations on different kind of perceptions in identifying a defect. In this paper, we intend to propose an object classification using a standard deviation value for classifying the defect on textile webs. First we describe the method of image segmentation that we applied in this study which is based on statistical technique. Further, we focus on the features analysis where we divide it into two phases; (1) learning phase and (2) analysis phase. Finally, we have been tested our propose algorithm into 5 (five) different types of textile webs with 500 images for each type of webs. We figure out that this method is suitable for distort and small defect as in textile webs. The details of results from our testing phases will be discussed at the end of this paper. |
| Starting Page | 376 |
| Ending Page | 376 |
| File Size | 195957 |
| Page Count | 1 |
| File Format | |
| ISBN | 0769528821 |
| DOI | 10.1109/ICICIC.2007.557 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-09-05 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image segmentation Image analysis Eyes Filtering Humans Inspection Feature extraction Image texture analysis Textile industry Testing |
| Content Type | Text |
| Resource Type | Article |
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