A novel SIFT-based codebook generation for handwritten Tamil character recognition

A Survey on Tamil Handwritten Character Recognition using OCR Techniques

“…Segmentation is categorized based on different stages as Projection based, Smearing, Grouping, Hough-based, graph-based and Cut Text Minimization (CTM). Modified cross counting Technique [10], Histogram profile [20] and connected component analysis are also found in the survey to handle the line character segmentation problem.…”

“…Normalization is the process of converting a random sized image into a standard size.The RoiExtraction [20] method is used to get the single structural element from the image. Bicubic interpolation [16], linear size normalization [14] and Java Image Class [12] normalization techniques could be used for standard sized images.…”

“…K-Nearest Neighbour approach [20] used as classifier to recognize the character sets and better accuracy. The result of the recognition is obtained using the Histogram Equalization.…”

“…Scale Invariant feature transform (SIFE) [20] is used to transfer the character image into a set of local features. Using this approach, 128 dimensions of SIFE features (Interesting points) are identified from the character image.…”

“…Segmentation of hand-written documents is more complex than type-written documents. Histogram profiles and connected component analysis [20] [6] are used for line segmentation. In segmentation process, paragraph space has been checked for identifying paragraphs.…”