Authors: Deepak Kumar and A. G. Ramakrishnan

Description: After correcting the word images by unwrapping, word images are preprocessed by scaling the height. Images with height less than 60 pixels are scale up by three time the original height, images with height more than 180 pixels are scaled to a standard height of 180 pixels and remaining images are unaltered.
Fischer discrimination factor is calculated for Red, Green, Blue, Intensity and Lightness planes with different power-law values [1]. The plane with maximum discrimination value is selected for segmentation .
Minimum value of image height and width, is used to pad zeros around the segmented image. Zeros padded images are passed to Omnipage OCR for word recognition.
[1] D. Kumar, M.N. Anil Prasad and A.G. Ramakrishnan, “NESP: Nonlinear enhancement and selection of plane for optimal segmentation and recognition of scene word images,” Proc. 20Th DRR, (2013).