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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Maslita Abd Aziz
Universiti Teknikal Malaysia Melaka

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Framework of diacritic segmentation for Arabic handwritten document Ahmed Abdalla Shiekh; Mohd Sanusi Azmi; Maslita Abd Aziz; Mohammed Nasser Al-Mhiqani; Salem Saleh Bafjaish
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp1001-1008

Abstract

In recent Arabic standard language and Arabic dialectal texts, diacritics and short vowels are absent. There are some exceptions have been made for the Arabic beginner learner scripts, religious texts and as well as a significant political text. In addition, the text without diacritics is considered ambiguous due to numerous words with different diacritic marks seem identical. However, this paper we present a framework for segmenting diacritics from Arabic handwritten document by using region-based segmentation technique. Since Arabic handwritten and Mushaf Al-Quran contain many diacritical marks. Hence, the diacritics must be properly extracted from Arabic handwritten document to avoid losing some good features. Furthermore, the proposed framework is devised specifically to segment diacritics from Arabic handwritten image, thus there will be no feature extraction, feature selection, and classification processes included. Besides, we will present the methodology that is used to fulfil the objectives of this paper. The pre-processing phases will be explained and more specifically segmentation phase for segmenting diacritics which is the phase we concentrate more in this article. Lastly, we will identify the proposed technique region-based segmentation to facilitate our development throughout the experimental process.
Improving the efficiency of clustering algorithm for duplicates detection Abdulrazzak Ali; Nurul Akmar Emran; Safiza Suhana Kamal Baharin; Zahriah Othman; Awsan Thabet Salem; Maslita Abd Aziz; Nor Mas Aina Md Bohari; Noraswaliza Abdullah
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1586-1595

Abstract

Clustering method is a technique used for comparisons reduction between the candidates records in the duplicate detection process. The process of clustering records is affected by the quality of data. The more error-free the data, the more efficient the clustering algorithm, as data errors cause data to be placed in incorrect groups. Window algorithms suffer from the window size. The larger the window, the greater the number of unnecessary comparisons, and the smaller the window size may prevent the detection of duplicates that are supposed to be within the window. In this paper, we propose a data pre-processing method that increases the efficiency of window algorithms in grouping similar records together. In addition, the proposed method also deal s with the window size problem. In the proposed method, high-rank attributes are selected and then preparators are applied to the selected traits. A compensation algorithm is implemented to reduce the problem of missing and distorted sort keys. Two datasets (compact disc database (CDDB) and MusicBrainz) were used to test duplicates detection algorithms. The duplicates detection toolkit(DuDe) was used as a benchmark for the proposed method. Experiments showed that the proposed method achieved a high rate of accuracy in detecting duplicates. In addition, the proposed method.
Co-Authors Abdulrazzak Ali Ahmed Abdalla Shiekh Awsan Thabet Salem Mohammed Nasser Al-mhiqani Mohd Sanusi Azmi Nor Mas Aina Md Bohari Noraswaliza Abdullah Nurul Akmar Emran Safiza Suhana Kamal Baharin Salem Saleh Bafjaish Zahriah Othman