27 research outputs found

    Handwritten Script Recognition using DCT, Gabor Filter and Wavelet Features at Line Level

    Get PDF
    In a country like India where more number of scripts are in use, automatic identification of printed and handwritten script facilitates many important applications including sorting of document images and searching online archives of document images. In this paper, a multiple feature based approach is presented to identify the script type of the collection of handwritten documents. Eight popular Indian scripts are considered here. Features are extracted using Gabor filters, Discrete Cosine Transform, and Wavelets of Daubechies family. Experiments are performed to test the recognition accuracy of the proposed system at line level for bilingual scripts and later extended to trilingual scripts. We have obtained 100% recognition accuracy for bi-scripts at line level. The classification is done using k-nearest neighbour classifier

    PUBLIC OCR SIGN AGE RECOGNITION WITH SKEW & SLANT CORRECTION FOR VISUALLY IMP AIRED PEOPLE

    Get PDF
    This paper presents an OCR hybrid recognition model for the Visually Impaired People (VIP). The VIP often encounters problems navigating around independently because they are blind or have poor vision. They are always being discriminated due to their limitation which can lead to depression to the VIP. Thus, they require an efficient technological assistance to help them in their daily activity. The objective of this paper is to propose a hybrid model for Optical Character Recognition (OCR) to detect and correct skewed and slanted character of public signage. The proposed hybrid model should be able to integrate with speech synthesizer for VIP signage recognition. The proposed hybrid model will capture an image of a public signage to be converted into machine readable text in a text file. The text will then be read by a speech synthesizer and translated to voice as the output. In the paper, hybrid model which consist of Canny Method, Hough Transformation and Shearing Transformation are used to detect and correct skewed and slanted images. An experiment was conducted to test the hybrid model performance on 5 blind folded subjects. The OCR hybrid recognition model has successfully achieved a Recognition Rate (RR) of 82. 7%. This concept of public signage recognition is being proven by the proposed hybrid model which integrates OCR and speech synthesizer

    Segmentation of Horizontally Overlapping Lines in Printed Indian Scripts

    Full text link

    Handwritten Devanagari Text Recognition using Single Classifier Approach with VSPCA Scheme

    Get PDF
    In this research paper we used individual classifier approach for Handwritten Devanagari text recognition. We experimented different categorical classifiers namely   Random Forest Classifier (RFC), Support Vector Machine (SVM), K Nearest Neighbor Classifier (KNN), Logistic Regression Classifier (LogRegr), Decision Tree Classifier (DTree). Seven different feature sets are used namely Eccentricity, Euler Number, Horizontal Histogram, Vertical Histogram, HOG Features, LBP Features, and Statistical Features. The experimentation is carried out on 9434 different characters whose features are extracted from 220 handwritten image documents from PHDIndic_11 dataset. We deduced and implemented a unique scheme namely VSPCA scheme. VSPCA is Vectorization, Scaling, and Principal Component Analysis carried out on all feature sets before being given for model training. We obtained varied accuracies using all these five classifiers on all these six feature sets in which 99.52% highest accuracy is observed
    corecore