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Assessment of Intermittent Leather based on Image Score Pattern

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Title Assessment of Intermittent Leather based on Image Score Pattern
 
Creator Vasagam, S Nithiyanantha
Sornam, M
 
Subject Intermittent Leather
Image Score Pattern
Gray Level Co-occurrence Matrix
Simple Linear Iterative Clustering
Support Vector Machine
 
Description 605-614
The process of intermittent leather inspection is being predominantly carried out with the support of human intervention
based on homogenous distribution of colors. However, results of the observations between one experts to another expert
may be different in opinion. Therefore, to emphasis some sort of supporting hand to the experts while taking decision, the
authors have introduced an algorithm based on Image Score Pattern to distinguish between defect versus non-defect
intermittent leather images. About 32 features generated from Gray Level Co-occurrence Matrix, Simple Linear Iterative
Clustering and Minimum Spanning Tree Clustering from the training and testing datasets of about 1132 and 404 generated.
The results of the classifier Support Vector Machine has confirmed the accuracy of 84% for the proposed Image Score
Pattern method for these datasets. Similarly, other performance measures such as Precision, Recall, F1-Score, Specificity
and Error Rate are also confirming that proposed method is performing in aligning of intermittent leather.
 
Date 2022-11-01T05:16:58Z
2022-11-01T05:16:58Z
2022-10
 
Type Article
 
Identifier 0971-4588 (Print); 0975-1017 (Online)
http://nopr.niscpr.res.in/handle/123456789/60760
https://doi.org/10.56042/ijems.v29i5.50542
 
Language en
 
Publisher NIScPR-CSIR,India
 
Source IJEMS Vol.29(5) [October 2022]