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Experimental Approach for Performance Analysis of Thinning Algorithms for Offline Handwritten Devnagri Numerals
Objectives: Performance and efficiency of thinning algorithms is essential in the field of image analysis and recognition. The present paper aims at experimental approach for performance analysis of different thinning algorithms for offline handwritten devnagri numeral script on multiparameter scale. Methods/Statistical Analysis: Algorithms based on datasets are reviewed and three algorithms based on their characteristics and strengths are implemented and their performance is evaluated based on pixel count in output image, compression ratio, pixel removal parameter, connectivity, triangle counts, unit pixel width, and information loss and topology preservation measure. Findings: Experimental findings indicate the strength and weakness of each thinning algorithm. Application/Improvements: The novelty of work is use of large parameter set for experimental performance evaluation. The findings and subsequent discussion aim at providing parametric strength of different thinning algorithms.
Devnagri Numeral, Handwritten Character Recognition, Skeleton, Thinning, Topology, Triangle Count, Unit Pixel Width.
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