Problems of the Arabic OCR: New Attitudes
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1 Problems of the Arabic OCR: New Attitudes Prof. O.Redkin, Dr. O.Bernikova Department of Asian and African Studies, St. Petersburg State University, St Petersburg, Russia Abstract - This paper reviews existing problems in the process of the Arabic OCR. By analyzing the traditional approaches to text recognition authors propose a model optimally considering the specificity of Arabic. OCR is a phased process and must include stages of initial analysis of the picture files including possible positions of graphemes sequence in accordance with the verbal or noun and decision on each of them in certain position. Ideally all the available databases should be used in the course of OCR process, among them - corpuses of texts, e-dictionaries, the Internet resources. The problem lies in the selection of the most relevant of them for the solution of a certain linguistic problem.. Keywords: Optical Character Recognition (OCR), Arabic 1 Introduction Optical Character Recognition (OCR) is among the most important problems of computer programming and mathematical linguistics. Most of the computer solutions designed for the Arabic OCR are based on the linear and vertical segmentation of the text with a subsequent identification of its separate components. The initial linear segmentation (lines) and the vertical segmentation (sentences, words and letters) is based on the use of the available information related to the nature of pixels of the *. bmp files. Although there is a sufficient amount of research on the problems of clusterization 1, the problem of OCR is far from its final solution. One of the reasons for it is that focusing on pure mathematical analysis restricts if not oversimplifies the 1 Avros R., Granichin O., Shalymov D., Volkovich Z., Weber G.-W. Randomized algorithm of finding the true number of clusters based on Chebychev polynomial approximation (Chapter 6) // Data Mining: Found. & Intell. Paradigms, D.E. Holmes, L.C. Jain (Eds.), Berlin Heidelberg: Springer-Verlag, ISRL 23, Vol. 1, pp Granichin O.N., Shalymov D.S., Avros R., Volkovich Z. A randomized algorithm for estimating the number of clusters // Automation and Remote Control, Vol. 72, No. 4, pp actual process of recognizing of the written text, and hence, limits the effectiveness of the software. Besides that it may also lead to errors, especially when the high level of random unwanted noises takes place (for example, insufficient quality of the handwritten or printed document - defects of paper or script, notes between the lines or on the original text, etc.). So it is necessary to understand the process of OCR broader than just a formal analysis and clusterization of the pixels. The initial stage of the optical recognition must be followed by the analysis of the possible positions of graphemes sequence in accordance with the verbal or noun and decision on each of them in a certain position. The selection of the correct characters in the range of the possible variants also depends on the results of lexical and syntax analysis within the framework of a syntagm. The ideal software for recognizing acoustic or written text must simulate the actual processes of one s reading and decoding of the written symbols (characters). However, there is no universal program so far which simulates the entire model of the native speaker reading process. Thus, the aim is to simulate the cognitive process of reading character recognition and its subsequent stages.. 2 Peculiarities of the Arabic Text The problem of the character recognition is twofold, and, along with the purely mathematical part there is a linguistic one. When solving such kind of problems collaboration of linguists and computer programmers gives good results in the creation of linguistically oriented computer programs if the project participants are well aware of difficulties and opportunities in both sectors of the task. Today, there is the effective OCR software developed for Latin or Cyrillic texts. As for the Arabic script, the problem seems to be more complex than for the two cases mentioned above. To a certain extent it is caused by the peculiarities of the Arabic script, among which one can mention a big number of morphological and graphic derivatives, cursive stile of writing, which presents a continuous flowing line, joined-up writing of many prepositions, particles, etc. Sometimes the elements of the characters (the dots) may be presented in disperse, and may be located apart from the main element of the letters.
2 The account of the peculiarities and difficulties may be followed by such factors as the variation of the certain written elements of the letters, size of the components, the presence of ligatures and the ability to write letters on the homepage, as well as differences in the shape of the elements of writing letters, slope, size, elements, etc. In addition, there are regional variants of the letters, for example instead of regular, and or instead of in Maghreb and letters used sporadically in dialectal or loanwords:,,. Besides that, as it is well known in the dialects the interdental spirants can be realized as the corresponding explosive such, instead of, instead of, and spirants instead of affricates, for example, instead of, or instead of, - the facts which are reflected in written texts. The problem of recognizing handwritten documents, especially manuscripts, which include the individual characteristics of the authors handwriting, is even more complex, not to mention the extra noises notes of the scribes, defects of the written material, and lacunae and gaps in the text, notes and additions to the original text. All this makes the correct identification of the Arabic written texts extremely difficult. So, despite the abundance of works and research materials dedicated to the problem of the Arabic OCR made up today, the problem is still far from to be resolved. In order to provide accuracy in the Arabic text recognition a set of special methods should be used along with the classical attitudes for optical character recognition. Among them there are such as developing of the grammatical and lexical analyzers, consideration of such useful data as the relative frequency of use of letters or words, the comparison with existing databases, such as e-dictionaries, software lemmatization, etc. 3 Formal Indicators for OCR Among the formal markers that facilitate the task of optical character recognition - are the spaces between words which allow to define the beginning and the end of the words. Besides that such characters as t -marbtah or alif lm of the definite article also indicate the beginning or the end of the word respectively. The minor spaces may help to identify such characters as alif, dl, dhl, r, zyn in medial position within the word. The frequency of characters or words use may be also regarded as one of the clues which affects the identification of the written elements. Thus the most frequent characters are more likely in certain position. As for the account of the frequency of letters, the analysis of the text of the Qur'an gives the following results: Character alif m n m w f ayn f alif maksra n l dhl djm hamzah kh marbta n d d zayn th ghayn Dth Tab. 1. Frequency of letters 2 Count The most frequent words As for the most frequent words the authors have carried on analysis of the texts including some one million words and the most frequent words are: Tab. 2. The most frequent words in Arabic conj. and prep. in prep. from prep. and conj. that which prep. to 2 mple.jsp
3 this (masc.) what prep. about sun this (fem.) year no prep. with that moon he to be each, all Statistical analysis is also one of the most effective methods used for the processing of the material in other languages, for example, Vietnamese Linguistic Context As it was mentioned above in addition to the methods of optical character recognition, in addition to form and grammatical and lexical analyzers, and consideration of other useful data, such as the relative frequency of use of letters or words, it is important to use available databases, such as e- dictionaries, e-translators, morphological and lexical analyzers, etc. A decision on the choice of a letter can be made subject to the rules of compatibility and incompatibility of letters in Arabic. 4 Moreover, unlike in most of the Indo-European languages where the text has linear character and represents the sequence of graphemes which correspond to certain phonemes, in Arabic the degree of hieroglyphic style of the text increases and, due to consonantal type of writing each word may represent various grammatical forms. The lower is the clarity and sharpness of writing is, the greater is the variability of the recognition and comprehension of its characters. Consonantal script without diacritics, which existed at the early stage, allowed a vast variety of characters identifications. Thus the same letter or word form could be recognized, understood and read in different ways. All this relates to old types of Arabic script, for example, ancient kufi script and the first written texts of the Qur'an. Tab. 3. Compatibility and incompatibility of letters in Arabic Character 1 Characters incompatible Character 1 with 3 Hieu L. T., Granichin O. N. Using application of statistics for word extraction from Vietnamese documents // Vestnik Sankt-Petersb. Univ. App. Math., No. 3, pp Yushmanov N.V. Grammatika literaturnogo arabskogo yazyka (The Grammal of Literary Arabic). St. Petersburg, P Picture 1. The Qur'an (kufi script). 5
4 in this position. So, another important condition of successful and comprehensive OCR is the analysis of grammatical and lexical context, including the semantics of the words, and, hence, modeling of all possible linguistic environments. Thus the OCR process along with the analysis of the linear sequence of its constituent units (sentences, words and, finally, letters) must include grammatical and lexical analyzers, i.e. the available lexical and morphological databases as well as take into consideration relevant linguistic and extralinguistic context clues. 3.3 Extralinguistic Context Picture 2. A fragment of the manuscript from the Manuscripts Collection at the Department of Oriental and African Studies, Saint-Petersburg State University. Commentaries to Az- Zinjani Grammar by At-Tantazani. Picture 3. A fragment of the manuscript from the Manuscripts Collection at the Department of Oriental and African Studies, Saint-Petersburg State University. At-Tantawi s Collection. Meanwhile variability of reading and comprehension of sacred texts, such as the text of the Qur'an is unacceptable, so diacritics (dots) and special signs for vowels were introduced later on. At the time of writing is not only omission of vowels, but the point above or below, making it difficult to adequately understand and read the text simultaneity of such a process. Thus the results of the first phase of the optical character recognition should be analyzed regarding the available databases and considering all possible derivates of the certain root and variants of word forms, which are possible In many respects the OCR software must resemble the cognitive process of the native speakers which is based on the basis of his/her prior linguistic and practical knowledge and experiences, which affects recognition and comprehension of the written text and have options for self learning. 6 Thus, the linguistic experience of a native speaker of the texts makes it possible to understand the words written unclear or in the defective way, for instance, including the omission of vowels, misspellings, etc., which, however, has only a negligible impact on their perception of the text or adequacy of reading. In a certain sense, the native speakers reading is heuristic by its nature, and is the result of many years of linguistic practice and, ultimately, fluent reading. Thus, in the course of the dialogue the extralinguistic context gives grammatical information related to such grammatical categories as person, gender, number, along with the information related to the choice of the most appropriate communication style, etc. In addition, the situation context and information related to the subject of the text gives clues related to the vocabulary used in it and thus limits the search fields in the e- dictionaries and databases. 4 Conclusions OCR is a phased process and must include stages of initial analysis of the picture files including possible positions of graphemes sequence in accordance with the verbal or noun and decision on each of them in a certain position. Ideally all the available databases should be used in the course of OCR process, among them - corpuses of texts, e-dictionaries, the Internet resources. The problem is in the selection of the most 6 Granichin, O.N.; Izmakova, O.A. A randomized stochastic approximation algorithm for self-learning // Automation and Remote Control. Volume: 66 Issue: 8 PP DOI: /s Aug
5 relevant of them for the solution of the certain linguistic problem. The software system must have access to extensive databases used for the identification of the characters, and finally, the word forms on the basis of the comparative analysis, and, if possible, be suitable for simulation of the model of actual text reading and comprehension. 4. References [1] Avros R., Granichin O., Shalymov D., Volkovich Z., Weber G.-W. Randomized algorithm of finding the true number of clusters based on Chebychev polynomial approximation (Chapter 6), Data Mining: Found. & Intell. Paradigms, D.E. Holmes, L.C. Jain (Eds.), Berlin Heidelberg:, ISRL 23, Vol. 1, , Springer-Verlag 2012 [2] Redkin O.I., Bernikova O.A., On the Optical Character Recognition and Machine Translation Technology in Arabic ; Proceedings of the 2011 International Conference on Artificial Intelligence. Las Vegas, USA, Pp [3] Granichin O.N., Shalymov D.S., Avros R., Volkovich Z. A randomized algorithm for estimating the number of clusters // Automation and Remote Control, Vol. 72, No. 4, pp [4] Hieu L. T., Granichin O. N. Using application of statistics for word extraction from Vietnamese documents, Vestnik Sankt-Petersb. No. 3, , [5] Yushmanov N.V. Grammatika literaturnogo arabskogo yazyka" (The Grammal of Literary Arabic). St. Petersburg, [6] Granichin, O.N.; Izmakova, O.A. A randomized stochastic approximation algorithm for self-learning, Automation and Remote Control. Vol.66, Issue 8, , Aug [7] Redkin O.I., Bernikova O.A., Shalymov D.S. Software for Arabic text e-learning, translation and recognition ; St.Petersburg, Russia, April 2007.
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