Zoning methods for handwritten character recognition: A survey
Pattern Recognition
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Zoning features are of the most popular and efficient statistical features that provide high speed and low complexity for character and word recognition. They are calculated by the density of pixels or pattern characteristics in several zones we divide the pattern frame. In this paper, we introduce the idea of adaptive zoning features that are extracted after adjusting the position of every zone based on local pattern information. This adjustment is performed by moving every zone towards the pattern body. This process is based on the maximization of the local pixel density around each zone. We have extensively tested our approach for character and word recognition as well as for using the pixel density or pattern characteristics in every zone. For all cases, we have recorded a significant improvement when the zoning features are used in the proposed adaptive way.