Neural Network Based Segmentation Algorithm for Arabic Characters Recognition
نویسنده
چکیده
This paper presents a novel holistic technique for classifying Arabic handwritten text documents, which it is performed in several steps. First, the Arabic handwritten document images are segmented into their connected parts. A simple heuristic segmentation algorithm is used which finds segmentation points in printed and cursive handwritten words. Second, several features are extracted from these connected parts and then combined to represent a word with one consolidated feature vector. Finally, Neocognitron type of the neural network is used to learn and classify the different fonts into word classes.
منابع مشابه
Handwritten Character Recognition using Modified Gradient Descent Technique of Neural Networks and Representation of Conjugate Descent for Training Patterns
The purpose of this study is to analyze the performance of Back propagation algorithm with changing training patterns and the second momentum term in feed forward neural networks. This analysis is conducted on 250 different words of three small letters from the English alphabet. These words are presented to two vertical segmentation programs which are designed in MATLAB and based on portions (1...
متن کاملNeural Network Based Recognition System Integrating Feature Extraction and Classification for English Handwritten
Handwriting recognition has been one of the active and challenging research areas in the field of image processing and pattern recognition. It has numerous applications that includes, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. Neural Network (NN) with its inherent learning ability offers promising solutions for handwritten characte...
متن کاملRecurrent Neural Network Method in Arabic Words Recognition System
The recognition of unconstrained handwriting continues to be a difficult task for computers despite active research for several decades. This is because handwritten text offers great challenges such as character and word segmentation, character recognition, variation between handwriting styles, different character size and no font constraints as well as the background clarity. In this paper pri...
متن کاملDocument Analysis And Classification Based On Passing Window
In this paper we present Document analysis and classification system to segment and classify contents of Arabic document images. This system includes preprocessing, document segmentation, feature extraction and document classification. A document image is enhanced in the preprocessing by removing noise, binarization, and detecting and correcting image skew. In document segmentation, an algorith...
متن کاملOn Arabic Character Recognition Employing Hybrid Neural Network
Arabic characters illustrate intricate, multidimensional and cursive visual information. Developing a machine learning system for Arabic character recognition is an exciting research. This paper addresses a neural computing concept for Arabic Optical Character Recognition (OCR). The method is based on local image sampling of each character to a selected feature matrix and feeding these matrices...
متن کامل