Malaysian Journal of Computer Science | |
Multiclass Test Feature Classifier for Texture Classification | |
Vakthang Lashkia1  Shun`ichi Kaneko1  Satoru Igarashi1  Itqon1  | |
关键词: Pattern recognition; Test feature classifier; Ill-class problem; Texture classification; Rank feature; | |
DOI : | |
学科分类:社会科学、人文和艺术(综合) | |
来源: University of Malaya * Faculty of Computer Science and Information Technology | |
【 摘 要 】
A new multi-class pattern classifier called ‘Test Feature Classifier�? is presented.It is based on training a recogniser by training samples of binary patterns and voting primitive scores depending on many trained templates called ‘test feature�?, which serves as local evaluation of the features.The method is non-metric and does not misclassify any patterns once learned previously.The two-class version of test feature classifier was of high performance for searching textual region in complex images.In this paper, we extend it to handle multi-class problems and apply it for solving ill-class problems in texture classification.We show the performance of the classifier on more than 1000 real images and compare it with a linear distance-based classifier and a non-linear distance-based classifier.The experimental results of both simulations and real applications show that the proposed classifier has better performance than conventional ones.
【 授权许可】
Unknown
【 预 览 】
Files | Size | Format | View |
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RO201912010262524ZK.pdf | 375KB | download |