Handwritten character recognition is always a frontier area of research in the field of pattern recognition and image processing and there is a large demand for OCR on hand written documents. Even though, sufficient studies have performed in foreign scripts like Chinese, Japanese and Arabic characters, only a very few work can be traced for handwritten character recognition of Indian scripts es...

Document layout analysis is an important task needed for handwritten text recognition among other applications. Text layout commonly found in handwritten legacy documents is in the form of one or more paragraphs composed of parallel text lines. An approach for handwritten text line detection is presented which uses machinelearning techniques and methods widely used in natural language processin...

during the fifth and sixth centuries a.h, the persian gulf faced a recession in its commerce; instead, the centrality of the international maritime trade was transferred to the red sea and mediterranean region at the time. emergence of the kish island, as a significant trade area in the persian gulf region goes back to the mid-sixth century a.h. efforts made by a local tribe known as bani qaysa...

This article concerns the spotting of regular expressions (REGEX) in handwritten documents using a hybrid model. Spotting REGEX in a document image allow to consider further extraction tasks such as document categorization or named entities extraction. Our model combines state of the art BLSTM recurrent neural network for character recognition and segmentation with a HMM model able to spot the ...

In many documents machine printed& handwritten texts are intermixed .Optical Character Recognition (OCR) techniques are different for machine printed and handwritten text, so it is necessary to separate these text before giving input to the OCR. In this paper we are proposing methodology for Hindi language. This methodology is based on structural features of text. Experimental results on a data...

We present in this paper a system of English handwriting recognition based on 40-point feature extraction of the character. Basically an off-line handwritten alphabetical character recognition system using multilayer feed forward neural network has been described in our work. Firstly a new method, called, 40-point feature extraction is introduced for extracting the features of the handwritten a...

Separating handwritten and machine printed text from a document has many applications. Various types of documents like bank cheques and forms etc. are used in daily life which contains both handwritten as well as printed text. It is necessary to separate handwritten and machine printed text before processing it with optical character recognition system. Various strategies are used to discrimina...

We describe our work on text-image alignment in context of building a historical document retrieval system. We aim at aligning images of words in handwritten lines with their text transcriptions. The images of handwritten lines are automatically segmented from the scanned pages of historical documents and then manually transcribed. To train automatic routines to detect words in an image of hand...

Handwriting recognition research requires large databases of word images each of which is labeled with the word it contains. Full images scanned in, however, usually contain sentences or paragraphs of writing. The creation of labeled databases of images of isolated words is usually tedious, requiring a person to drag a rectangle around each word in the full image and type in the label. Transcri...