|Title:||The extended-average common submatrix similarity measure with application to handwritten character images||Journal:||Informatica (Netherlands)||Volume:||29||Issue:||3||First page:||399||Last page:||420||Issue Date:||1-Jan-2018||Rank:||M21||ISSN:||0868-4952||DOI:||10.15388/Informatica.2018.173||Abstract:||
This paper introduces a new similarity measure derived from the Common Submatrix-based measures for comparing square matrices. The novelty is that the similarity between two matrices is computed as the average area of the largest sub-matrices exactly matching and being located at the same position in the two matrices. By contrast, in the original similarity measures, the largest sub-matrices can exactly or approximately match and be located at different positions. An experiment conducted on a subset of the MNIST and NIST datasets shows that the new similarity measure is very promising in retrieving relevant handwritten character images.
|Keywords:||2d array | characters recognition | image processing | pattern matching | similarity||Publisher:||Vilnius University||Project:||Development of new information and communication technologies, based on advanced mathematical methods, with applications in medicine, telecommunications, power systems, protection of national heritage and education
Development and application of distributed system for monitoring and control of electrical energy consumption for large consumers
Show full item record
checked on Sep 16, 2022
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.