Abstract
Homomorphic transforms are better suited for pattern recognition or classification. In general, homomorphic maps are not invertible and hence they are known as transformations. So, they do not fall under the category of mathematical transforms. But if the inverse of a transformation is obtained using an algorithm or a semi-decision procedure the transformation could be called a transform in the loose sense. Nonlinear homomorphic operators are not meant for analysis and synthesis, but they are used for classification. In this context, efforts were made to search for a homomorphic map which could be examined for character recognition. One such nonlinear homomorphic map has been identified as Rajan Transform. This paper provides details of this transform and its working principle in recognition of handwritten characters.
Highlights
Handwritten Character Recognition (HCR) is an important but most challenging task in the field of pattern recognition with huge number of practical applications
Rajan Transform is structurally similar to Hadamard Transform, but it functionally differs from the latter in the sense that it generates phasor information during different stages of computation, and it works as an isomorphic function with the phasor information and it works as a homomorphic function without the phasor information
Neighborhood processing and mathematical morphological processing of digital images are the two basic paradigms in which a number of feature extraction techniques and algorithms have been developed for pattern recognition purposes
Summary
Handwritten Character Recognition (HCR) is an important but most challenging task in the field of pattern recognition with huge number of practical applications. Rajan Transform is structurally similar to Hadamard Transform, but it functionally differs from the latter in the sense that it generates phasor information during different stages of computation, and it works as an isomorphic function with the phasor information and it works as a homomorphic function without the phasor information. This homomorphic property is made use of for the purpose of pattern classification. A number sequence and its dual are like an object and its mirror image [1]
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