Intelligent word recognition

About: Intelligent word recognition is a research topic. Over the lifetime, 2480 publications have been published within this topic receiving 45813 citations.

Segmentation and coding of Arabic handwritten words

Abstract: We propose a segmentation method and handwritten word coding method by human observation for automatic document processing in Arabic. The system is composed of three levels. The first level deals with the word segmentation into portions of characters called graphemes. The second level analyses these graphemes and codes the word by a sequence of observations similar to human perception. The results of these two levels are used in the recognition level (the third level) which are presented as perspective in this paper.

Cursive script segmentation with neural confidence

Abstract: This paper presents a new, simple and fast approach for character segmen- tation of unconstrained handwritten words. The proposed approachrst seeks the possible character boundaries based on characters geometric features analysis. However, due to inherited ambiguity and a lack of context, few characters are over-segmented. To increase the efficiency of the proposed approach, an Articial Neural Network is trained with sig- nicant number of valid segmentation points for cursive handwritten words. Trained neural network extracts incorrect segmented points efficiently with high speed. For fair comparison, benchmark database CEDAR is used. The experimental results are promis- ing from complexity and accuracy points of view. Keywords: Handwriting recognition, Character segmentation, Feature extraction, Char- acter recognition, Back propagation learning

Defining writer's invariants to adapt the recognition task

Abstract: Investigates the automatic reading of unconstrained omni-writer handwritten texts. This paper shows how to endow the reading system with adaptation faculties for each writer's handwriting. The adaptation principles are of major importance for making robust decisions when neither simple lexical nor syntactic rules can be used, e.g. for a free lexicon or for full text recognition. The first part of this paper defines the concept of writer's invariants. In the second part, we explain how the recognition system can be adapted to a particular handwriting by exploiting the graphical context defined by the writer's invariants. This adaptation is guaranteed, thanks to the writer's invariants, by activating interaction links over the whole text between the recognition procedures for word entities and those for letter entities.

On-line handwritten character pattern database sampled in a sequence of sentences without any writing instructions

Abstract: The paper presents a database of on-line handwritten character patterns sampled in a sequence of sentences without any instructions. The sentences according to which character patterns are collected have been picked up from newspaper to include 1227 frequently appearing character categories with the result that they are composed of about 10000 characters and include 1537 JIS 1st level character categories. The rest of the JIS 1st level 1808 categories have been added at the end of the above text and written one by one. The total text has been commonly employed for collecting script patterns from a number of people. Patterns offered were inspected and omissions and wrong patterns were rewritten. The authors collected data from 80 people and made the 12000/spl times/80 patterns available from February 1996. More patterns are being collected. The paper describes the characteristics of this database as well as several tools to collect patterns.