Rached Zantout

Peak position recognizing characters in Saudi license plates

In this paper character recognition in Saudi Automobile License Plates is described. Due to special properties of Saudi license plates, simpler procedures as compared to the ones used for Lebanese plates have been developed. A limited character set for recognition enables the development of smaller recognition trees. The developed procedure was applied to different characters taken from real license plates and the recognition rate was 100% for characters supported by the algorithm. Uniformly distributed pseudo-random noise was added to simulate error in the image. The algorithm was proven to work even in cases in which the characters were extremely degraded by noise.

Fleet management automation using the global positioning system

Fleet management is an important topic in research and development nowadays. Companies, security and emergency forces need to keep track of their trucks and cars and know where a vehicle is at a moment in time, and when, where and for how long a vehicle stopped.

License Plate Localization in ALPR Systems

In this paper, an approach to vehicle license plate localization is described. The algorithm starts by isolating objects, in the image, that can be possible candidates of characters in a license plate. It then uses distances between objects and their relative positions to identify possible groupings (series) of characters that could belong to a license plate. The algorithm then uses a novel character recognition approach to recognize the identity of each character in the series. Finally, the relative positions of series are used to localize the license plate. The algorithm was successfully applied to images containing Lebanese license plates.

A Methodology for Evaluating Arabic Machine Translation Systems

Abstract.This paper presents a methodology for evaluating Arabic Machine Translation (MT) systems. We are specifically interested in evaluating lexical coverage, grammatical coverage, semantic correctness and pronoun resolution correctness. The methodology presented is statistical and is based on earlier work on evaluating MT lexicons in which the idea of the importance of a specific word sense to a given application domain and how its presence or absence in the lexicon affects the MT system’s lexical quality, which in turn will affect the overall system output quality. The same idea is used in this paper and generalized so as to apply to grammatical coverage, semantic correctness and correctness of pronoun resolution. The approach adopted in this paper has been implemented and applied to evaluating four English-Arabic commercial MT systems. The results of the evaluation of these systems are presented for the domain of the Internet and Arabization.

Recognizing characters in Saudi License Plates using character boundaries

In this paper character recognition in Saudi Automobile License Plates is described. Due to special properties of Saudi license plates, simpler procedures as compared to the ones used for Lebanese plates have been developed. A limited character set for recognition enables the development of smaller recognition trees. The developed procedure was applied to different characters taken from real license plates and the recognition rate was 100% for characters supported by the algorithm. Uniformly distributed pseudo-random noise was added to simulate error in the image. The algorithm was proven to work even in cases in which the characters were extremely degraded by noise.

Automatic processing of Arabic text

Automatic recognition of printed and handwritten documents remains an active area of research. Arabic is one of the languages that present special problems. Arabic is cursive and therefore necessitates a segmentation process to determine the boundaries of a character. Arabic characters consist of multiple disconnected parts. Dots and Diacritics are used in many Arabic characters and can appear above or below the main body of the character. In Arabic, the same letter has up to four different forms depending on where it appears in the word and depending on the letters that are adjacent to it. In this paper, a novel approach is described that recognizes Arabic script documents. The method starts by preprocessing which involves binarization, noise reduction, and thinning. The text is then segmented into separate lines. Characters are then segmented by determining bifurcation points that are near the baseline. Segmented characters are then compared to prestored templates to identify the best match. The template comparisons are based on central moments, Hu moments, and Invariant moments. The method is proven to work satisfactorily for scanned printed Arabic text. The paper concludes with a discussion of the drawbacks of the method, and a description of possible solutions.

An automatic English-Arabic HTML page translation system

The Internet and the World Wide Web have become an integral part of everyday life, an important source of information and a communication medium. One of the main problems confronting non-English speakers in using the Internet is that it is heavily dominated by the English language. Knowledge of English is a prerequisite for using the Web efficiently and benefiting from the multitude of services it offers. This paper introduces the approach underlying a prototype system that translates Web pages from English to Arabic automatically. The system uses a commercial machine translation system to translate the textual part of a Web page. It then displays a Web page containing the Arabic translation with all tags inserted in the right places so that the layout and content of the original (English) page are preserved.

Power management in virtualized data centers: state of the art

Cloud computing is an emerging technology in the field of computing that provides access to a wide range of shared resources. The rapid growth of cloud computing has led to establishing numerous data centers around the world. As data centers consume huge amounts of power, enhancing their power efficiency has become a major challenge in cloud computing. This paper surveys previous studies and researches that aimed to improve power efficiency of virtualized data centers. This survey is a valuable guide for researchers in the field of power efficiency in virtualized data centers following the cloud computing model.

Error Correction of Noisy Block Cipher Using Cipher and Plaintext Characteristics

Contemporary proven cryptographic algorithms, like the Advanced Encryption Standard (AES), are used in many secure data storage systems. Cipher data when written or read might be subject to noise. Classical error detection and correction methods are not suitable for encrypted data. In this paper, error detection and correction is performed at the receiver end, without any changes to the encryption algorithm. One of the properties of encrypted information is that all encrypted blocks have a minimum hamming distance from each other. This property is exploited to obtain the exact correct block. When error correction based on the encrypted data cannot be performed, natural language properties of plaintext data are used to eliminate noise. The plaintext blocks surrounding the noisy plaintext block are used to generate possible candidates. In case a unique solution is not achieved, n-gram properties of the plaintext language are used to rank the possibilities and promote the best fit.

Arabic Morphological Generation and its Impact on the Quality of Machine Translation to Arabic

The aim of this chapter is to highlight the complexity and importance of Arabic morphological information in an Arabic Machine Translation (AMT) system, i.e. a system that translates to or from Arabic. We summarize Arabic morphology and introduce the main morphological information that we have found relevant to machine translation to Arabic and categorize it into various types of features. In order to show the impact of these morphological features on machine translation quality, we have adopted an approach whereby we relate each of them to the quality of the translation. This leads us, through a statistical analysis of the test data, to a characterization of which features are more important in terms of their impact on the quality of the translation of a given AMT system (AMTS). The approach has been implemented and applied to evaluating an English-to-Arabic web-based MT system. The results of the evaluation of this system are presented, conclusions are drawn, and recommendations for improving their outputs made.