Freeman chain code histogram and Gradient feature extraction techniques are better because freeman chain code approach is robustness to small variation and easy to implement and the gradient technique can be easily used to gray scale images and are robust against image noise and edge direction fluctuation. SVM classifier is better than KNN and ANN classifier because of its complexity of training, flexibility, classification accuracy and complexity which is given bellow. | ISSN:2249-5789 Leena Y Rane et al , International Journal of Computer Science & Communication Networks,Vol 4(3),76-83 Offline Marathi Handwritten Character Recognition Using SVM Classifier Based on Cloud Computing: Review Sanjay S. Gharde Asst. Professor SSBT COET, Jalgaon sanjay_gharde358@ Mob:-9422344964 Abstract Handwritten recognition has been one of the active and challenging research areas in the field of image processing. However, most of the current work in these areas is limited to English and a few oriental languages with single computer. Many systems and classification algorithms have been proposed in the past years on handwritten characters recognition in various languages like English, Persian, Arabian and Devanagari scripts also. Researchers had been worked on Handwritten Devanagari characters by applying different techniques on single PC but using client and server recognize the Marathi handwritten character based on cloud computing is challenging. Previously researchers had been worked on online Chinese characters based on cloud computing. So, this research work has been conducted on offline Marathi Handwritten character based on cloud computing and this system is very important because person can access any data from anywhere. There are various feature extraction techniques and classifiers for recognition of Marathi characters but Freeman chain code histogram and Gradient feature extraction techniques are better because freeman chain code approach is robustness to small variation and easy to implement and the gradient technique can be easily used to gray scale images and are robust against image noise and edge direction fluctuation. SVM classifier is better than KNN and ANN classifier because of its complexity of training, flexibility, classification accuracy and complexity which is given bellow. Keywords Devnagari Marathi Character Recognition, Off-line Handwriting Recognition, Pre-processor, Feature Extraction, Image .
