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Objective Evaluation of Seam Pucker Using an Adaptive Neuro-fuzzy Inference System
| Content Provider | Semantic Scholar |
|---|---|
| Author | Mak, K. L. Li, Wenting |
| Copyright Year | 2010 |
| Abstract | Seam pucker evaluation plays a very important role in the garments manufacturing industry. At present, seam puckers are usually evaluated by human inspectors, which is subjective, unreliable and timeconsuming. With the developments of image processing and pattern recognition technologies, an automatic vision-based seam pucker evaluation system becomes possible. This paper presents a new approach based on adaptive neuro-fuzzy inference system (ANFIS) to establish the relationship between seam pucker grades and textural features of seam pucker images. The evaluation procedure is performed in two stages: features extraction with the co-occurrence matrix approach, and classification with ANFIS. Experimental results demonstrate the validity and effectiveness of the proposed ANFIS-based method. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.scitepress.org/papers/2008/10809/10809.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Adaptive neuro fuzzy inference system CNS disorder Clothing Co-occurrence matrix Document-term matrix Evaluation Grade Image processing Inference engine Neuro-fuzzy Pattern recognition Seam carving |
| Content Type | Text |
| Resource Type | Article |
