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Paper Information

Journal:   JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ)   SUMMER 2006 , Volume 33 , Number 1 (43) ELECTRICAL ENGINEERING; Page(s) 1 To 11.
 
Paper: 

CLUSTERING OF PRINTED FARSI SUBWORDS USING CHARACTERISTIC LOCI FEATURES AND K-MEANS ALGORITHM

 
 
Author(s):  EBRAHIMI AFSHIN, KABIR E.A.
 
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Abstract: 

In this paper the characteristic loci features are used for the description of printed Farsi subwords. In extraction of these features, the numbers of crossings with subword bodies are restricted to 2. Using PCA, 12 uncorrelated features are selected. The images of subwords are clusterd using k-means algorithm with Euclidian distance. 9445 subwords of Lotus 12 font, with 400dpi resolution, are clustered to 150 and 300 clusters. Minimum and maximum cluster sizes are 11 and 91 subwords, respectively, for 150 clusters and 2 and 58 subwords, for 300 clusters. In a test, for clustering verification, images of 200 subwords, were rescanned and classified to 300 clusters. In this classification, the Euclidian distance from cluster means is used. In first, first five and first ten choices, 80.69%, 97.52% and 100% of these subwords were correctly classified.

 
Keyword(s): SUBWORD, CHARACTERISTIC LOCI FEATURES, CLUSTERING, K-MEANS, PCA, CLASSIFICATION, EUCLIDIAN DISTANCE
 
 
References: 
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+ Click to Cite.
APA: Copy

EBRAHIMI, A., & KABIR, E. (2006). CLUSTERING OF PRINTED FARSI SUBWORDS USING CHARACTERISTIC LOCI FEATURES AND K-MEANS ALGORITHM. JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ), 33(1 (43) ELECTRICAL ENGINEERING), 1-11. https://www.sid.ir/en/journal/ViewPaper.aspx?id=103076



Vancouver: Copy

EBRAHIMI AFSHIN, KABIR E.A.. CLUSTERING OF PRINTED FARSI SUBWORDS USING CHARACTERISTIC LOCI FEATURES AND K-MEANS ALGORITHM. JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ). 2006 [cited 2021May16];33(1 (43) ELECTRICAL ENGINEERING):1-11. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=103076



IEEE: Copy

EBRAHIMI, A., KABIR, E., 2006. CLUSTERING OF PRINTED FARSI SUBWORDS USING CHARACTERISTIC LOCI FEATURES AND K-MEANS ALGORITHM. JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ), [online] 33(1 (43) ELECTRICAL ENGINEERING), pp.1-11. Available: https://www.sid.ir/en/journal/ViewPaper.aspx?id=103076.



 
 
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