NDLI: Investigating Jaccard Distance similarity measurement constriction on handwritten pen-based input digit

Content Provider	IEEE Xplore Digital Library
Author	Noor Aznimah Abdul Aziz Siti Salwa Salleh Mohamad, Daud Omar, Megawati
Copyright Year	2010
Description	Author affiliation: Research Management Institute, University Technology MARA, Shah Alam, Malaysia (Omar, Megawati) \|\| Department of Computer Science, Faculty of Computer and Mathematical Sciences, University Technology MARA, Shah Alam, Malaysia (Noor Aznimah Abdul Aziz; Siti Salwa Salleh) \|\| Department of Mathematics, Faculty of Computer and Mathematical Sciences, University Technology MARA, Shah Alam, Malaysia (Mohamad, Daud)
Abstract	This paper presents a preliminary study on conventional Jaccard Distance performance in recognizing shapes with and without pre processing tasks. This study also identified the pre processing tasks that should be conducted to improve recognition performance. Jaccard Distance is performed by measuring the asymmetric information on binary variable and the comparison between vectors component. It compared two objects and notified the degree of similarity of these objects. This study also evaluated recognition performance on hand writing on isolated digits written using pen-based device. The first part of the work showed low recognition performed by the conventional Jaccard Distance when there was no pre processing task done onto the input. However, after translation, rotation, invariance scale content and noise resistance were added it showed improvement on the recognition progress. However the improvement was not very significance. Result showed that the degree of accuracy only improve averagely by 20%. Therefore thorough pre-processing tasks are to be carried out for the pen-based input using Jaccard Distance measurement.
Starting Page	1181
Ending Page	1185
File Size	248072
Page Count	5
File Format	PDF
ISBN	9781424489879
e-ISBN	9781424489862
DOI	10.1109/CSSR.2010.5773712
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-05
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Handwriting recognition IEEE Computer Society Shape Shape measurement Noise Jaccard Distance Writing Similarity measurement Distance measures Pixel Shape recognition
Content Type	Text
Resource Type	Article

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