Complexities and Implementation Challenges in Offline Urdu Nastaliq OCR (original) (raw)
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Offline Urdu OCR using Ligature based Segmentation for Nastaliq Script
There are two most popular writing styles of Urdu i.e. Naskh and Nastaliq. Considering Arabic OCR research, ample amount of work has been done on Naskh writing style; focusing on Urdu, which uses Arabic character set commonly used Nastaliq writing style. Due to Nastaliq writing style, Urdu OCR poses many distinct challenges like compactness, diagonal orientation and context character shape sensitivity etc., for OCR system to correctly recognize the Urdu text image. Due to compactness and slanting nature of Nastaliq writing style, existing methods for Naskh style would not give desirable results. Therefore, in this paper, we are presenting ligature based segmentation OCR system for Urdu Nastaliq script. We have discussed in detail various unique challenges for the Urdu OCR and different feature extraction techniques for Ligature recognition using SVM and kNN classifier. The system is trained to recognize 11,000 Urdu ligatures. We have achieved overall 90.29% accuracy tested on Urdu text images.
Improving Nastalique specific pre-recognition process for Urdu OCR
2009 IEEE 13th International Multitopic Conference, 2009
Urdu language is written using Arabic script in Nastalique writing style. Nastalique script is highly cursive, context sensitive and is hard to process as only the last character in its ligature sits on the baseline. In addition, it exhibits character and ligature level spatial overlap. Due to these factors, the placement of dots and other diacritics is also highly contextual and variable. There is now increasing amount of work to process and recognize Nastalique script to develop Urdu OCR. This paper proposes improvements to these methods. The paper focuses on Nastalique specific pre-processing methods which can be employed before the text recognition process. The recognition and post recognition processes will be addressed separately.
Urdu Optical Character Recognition Technique for Jameel Noori Nastaleeq Script
Journal of Independent Studies and Research - Computing
Urdu OCR's have been an object of interest for many developers in the recent years. Active research is being done pertaining to Urdu OCR's, but because of the complexity associated with Urdu fonts; it still lacks perfection halting it from coming up to the surface. The main objective was to create a technique that could be applied to any of the existing Urdu fonts/scripts. In this paper, the authors have developed a technique which is capable of extracting the Urdu font "Jameel Noori Nastaleeq" from images and converts it into editable textual Unicodes. The approach comprises of pre-processing techniques, label connected components, feature extraction, and image comparison. The identified objects are saved as templates which are then compared to the white pixel position length database created by the authors in order to identify the templates which are then converted into Unicode.
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The development of Urdu Nastalique O Character Recognition (OCR) is a challenging task due to the cursive nature of Urdu, complexities of Nastalique writing style and layouts of Urdu document images. In this paper, the framework of Urdu Nastalique OCR is presented. The presented system supports the recognition of Urdu Nastalique document images having font size between 14 to 44. has 86.15% ligature recognition accuracy tested on 224 document images.
Ocr For Printed Urdu Script Using Feed Forward Neural Network
2007
This paper deals with an Optical Character Recognition system for printed Urdu, a popular Pakistani/Indian script and is the third largest understandable language in the world, especially in the subcontinent but fewer efforts are made to make it understandable to computers. Lot of work has been done in the field of literature and Islamic studies in Urdu, which has to be computerized. In the proposed system individual characters are recognized using our own proposed method/ algorithms. The feature detection methods are simple and robust. Supervised learning is used to train the feed forward neural network. A prototype of the system has been tested on printed Urdu characters and currently achieves 98.3% character level accuracy on average .Although the system is script/ language independent but we have designed it for Urdu characters only.
Urdu Nastaleeq Optical Character Recognition
2007
This paper discusses the Urdu script characteristics, Urdu Nastaleeq and a simple but a novel and robust technique to recognize the printed Urdu script without a lexicon. Urdu being a family of Arabic script is cursive and complex script in its nature, the main complexity of Urdu compound/connected text is not its connections but the forms/shapes the characters change when it is placed at initial, middle or at the end of a word. The characters recognition technique presented here is using the inherited complexity of Urdu script to solve the problem. A word is scanned and analyzed for the level of its complexity, the point where the level of complexity changes is marked for a character, segmented and feeded to Neural Networks. A prototype of the system has been tested on Urdu text and currently achieves 93.4% accuracy on the average.
The optical character recognition of Urdu-like cursive scripts
We survey the optical character recognition (OCR) literature with reference to the Urdu-like cursive scripts. In particular, the Urdu, Pushto, and Sindhi languages are discussed, with the emphasis being on the Nasta'liq and Naskh scripts. Before detaining the OCR works, the peculiarities of the Urdu-like scripts are outlined, which are followed by the presentation of the available text image databases. For the sake of clarity, the various attempts are grouped into three parts, namely: (a) printed, (b) handwritten, and (c) online character recognition. Within each part, the works are analyzed par rapport a typical OCR pipeline with an emphasis on the preprocessing, segmentation, feature extraction, classification, and recognition.
Multilingual OCR systems for the regional languages in Balochistan
Indian Journal of Science and Technology
Background: There are various languages for which an optical character recognition technology has been developed but most of these address a particular language and thereby multilingual OCR remains a challenge. Methods: Development of multilingual OCR is one of a highly debated issue. Researcher are studying the feasibility and operational feasibility of multilingual OCR from technical as well as from viable aspects. Multilingual OCR includes printed or handwritten characters' form. In this paper, we study the significance, challenges and issues of developing multilingual OCR system for regional language based on Persio-Arabic script by conducting a comprehensive survery about the operational viability of mmultilingual OCR. Findings: A feedback of 339 participants is collected through an online surgery to find the scope and applicability of multilingual OCR. The respondents were from different linguistic background. The study identified that a large majority of participants are willing to use their native language for the accomplishment of their computational task and deemed that the support of multiple languages in a software would increase their productivity. Novelty: In current form, the study addresses the viability of multilingual OCR of regional language based on Persio-Arabic script. To the best of our knowledge, such kind of study has not been conducted for the domain of Pakistan.
Optical Character Recognition or OCR is the electronic translation of handwritten, typewritten or printed text into machine translated images. Optical Character Recognition (OCR) is a very important task in Pattern Recognition. Foreign languages, especially English character recognition has been extensively studied by many researches but due to complication of Indian Languages like Hindi ,Punjabi ,teulgu ,malyalam etc. the research work is very limited and constrained. This paper presents the research work related to all Indian languages, various approaches to character recognition along with some applications of character recognition is also discussed in this paper. The aim of this paper is to provide an overview of the research going on in Indian script OCR systems. This survey paper has been felt necessary when the research on OCRs for Indian scripts is still a challenging task. Hence, a brief introduction to the general OCR and typical steps in the development of an OCR are give...