Name
Title | ||
|---|---|---|
A model of saliency-based selective attention for machine vision inspection application |
Abstract | ||
|---|---|---|
A machine vision inspection model of surface defects, inspired by the methodologies of neuroanatomy and psychology, is investigated. Firstly, the features extracted from defect images are combined into a saliency map. The bottom-up attention mechanism then obtains "what" and "where" information. Finally, the Markov model is used to classify the types of the defects. Experimental results demonstrate the feasibility and effectiveness of the proposed model with 94.40% probability of accurately detecting of the existence of cropper strips defects. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-20267-4_13 | ICANNGA (2) |
Keywords | Field | DocType |
markov model,machine vision inspection application,defect image,bottom-up attention mechanism,cropper strips defect,saliency-based selective attention,surface defect,saliency map,machine vision inspection model,selective attention,feature extraction,bottom up,machine vision | Computer vision,Saliency map,Pattern recognition,Machine vision,Computer science,Salience (neuroscience),Markov model,Selective attention,Artificial intelligence,Machine learning | Conference |
Volume | ISSN | Citations |
6594 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 5 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiao Feng Ding | 1 | 149 | 11.52 |
| Xu Lizhong | 2 | 155 | 24.51 |
| Xue-Wu Zhang | 3 | 43 | 11.98 |
| Fang Gong | 4 | 8 | 0.85 |
| Aiye Shi | 5 | 31 | 5.76 |
| Huibin Wang | 6 | 29 | 10.99 |