Automatic Handwritten Devanagari Text Generation in Marathi Styles using Ant Miner Algorithm

Abstract

The Devanagari scripts forms the backbone of the writing system of several Indian languages includes Hindi, Sanskrit and Marathi. With the increased demand, exploration and globalization of digital Devanagari documents, different printed and handwritten document recognition techniques have involved since last two decades. In literature many methods of Devanagari script recognition have been used but it is not able to attain the best results in recognition. Hence, in this paper is proposed Ant Miner Algorithm (AMA) for recognition and text generation of handwritten Devanagari Marathi Scripts. The proposed method recognition process is working with the four different stages such as pre-processing, segmentation, feature extraction and recognition with text generation. The first stage pre-processing is consists of skew correction, noise removal and binarization. The second stage is segmentation that contains the line segmentation, word segmentation and character segmentation. The third stage is feature extraction method it contains four methods such as Scale Invariant Feature Transform (SIFT), Linear Discriminant Analysis (LDA), Discrete Cosine Transform (DCT) and Local Binary Pattern (LBP). The final stage is recognition and text generation with attain with the help of AMA algorithm. It works based on the two phases such as training and testing phase. The proposed method is implemented in the python platform and it compared with the Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN). The performance of the proposed method is analysed with statistical measurements of accuracy, precision and recall.