Optical character recognition

About: Optical character recognition is a research topic. Over the lifetime, 7342 publications have been published within this topic receiving 158193 citations. The topic is also known as: OCR & optical character reader.

Offline handwritten Malayalam Character Recognition based on chain code histogram

Abstract: Optical Character Recognition plays an important role in Digital Image Processing and Pattern Recognition. Even though ambient study had been performed on foreign languages like Chinese and Japanese, effort on Indian script is still immature. OCR in Malayalam language is more complex as it is enriched with largest number of characters among all Indian languages. The challenge of recognition of characters is even high in handwritten domain, due to the varying writing style of each individual. In this paper we propose a system for recognition of offline handwritten Malayalam vowels. The proposed method uses Chain code and Image Centroid for the purpose of extracting features and a two layer feed forward network with scaled conjugate gradient for classification.

Lexical Search Approach for Character-String Recognition

Abstract: A novel method for recognizing character strings, based on a lexical search approach, is presented. In this method, a character string is recognized by searching for a sequence of segmented patterns that fits a string in a lexicon. A remarkable characteristic of this method is that character segmentation and character classification work as subfunctions of the search. The lexical search approach enables the parameters of character classifier to adapt to each segmented pattern. As a result, it improves the recognition accuracy by omitting useless candidates of character classification and by changing the criterion of rejection dynamically. Moreover, the processing time is drastically reduced by using minimum sets of categories for each segmented pattern. The validity of the developed method is shown by the experimental results using a lexicon including 44,700 character strings.

Arabic Character Recognition: Progress and Challenges

Abstract: An optical character recognition (OCR) system may provide a solution to the data entry problems, a bottleneck for the data processing industry. Therefore, OCR systems are being developed for almost all major languages and Arabic language is no exception to it. During the past three decades, considerable research and development works have been done towards the development of an efficient Arabic optical character recognition (ACR) system. In this paper we present a comprehensive review of ACR techniques and evaluate the status of the ACR system development and an up to date bibliography.

Probabilistic model for segmentation based word recognition with lexicon

Abstract: We describe the construction of a model for off-line word recognizers based on over-segmentation of the input image and recognition of segment combinations as characters in a given lexicon word. One such recognizer, the Word Model Recognizer (WMR), is used extensively. Based on the proposed model it was possible to improve the performance of WMR.

Indigenous language technologies in Canada: Assessment, challenges, and successes

Abstract: In this article, we discuss which text, speech, and image technologies have been developed, and would be feasible to develop, for the approximately 60 Indigenous languages spoken in Canada. In particular, we concentrate on technologies that may be feasible to develop for most or all of these languages, not just those that may be feasible for the few most-resourced of these. We assess past achievements and consider future horizons for Indigenous language transliteration, text prediction, spell-checking, approximate search, machine translation, speech recognition, speaker diarization, speech synthesis, optical character recognition, and computer-aided language learning.