No abstract

Arabic is a broadly utilized alphabetic composition framework on the planet, and it has 28 essential letters. The letters in order was first used to compose messages in Arabic, most prominently the Qur'an the holy book of Islam. However, Arabic language has diacritics in the word or letters which are not something extra or discretionary to the language, rather they are a vital piece of it. By changing some diacritics may change both the syntax and semantics of a word by turning a word into another. However, the current researches address the foreground image and consider the diacritics as noises or secondary images. Thus, it is not suitable for Arabic handwritten. The diacritics will be removed from the image and this will lead to losing some good features.   Furthermore, to extract the diacritics, the region-based segmentation technique is used. The image will be measured based on the region properties by first finding the connected component in binary image, and then we will determine the best area range measurement in that region for each image. The proposed technique region based has been tested in nine different images with different handwritten style, and successfully extracted secondary foreground images (diacritics) for each image.

Skew correction have been studied a lot recently. However, the content of skew correction in these studies is considered less for Arabic scripts compared to other languages. Different scripts of Arabic language are used by people. Mushaf A-Quran is the book of Allah swt and used by many people around the world. Therefore, skew correction of the pages in Mushaf Al-Quran need to be studied carefully. However, during the process of scanning the pages of Mushaf Al-Quran and due to some other factors, skewed images are produced which will affect the holiness of the Mushaf Al-Quran. However, a major difficulty is the process of detecting the skew and correcting it within the page. Therefore, this paper aims to view the most used skew correction techniques for different scripts as cited in the literature. The findings can be used as a basis for researchers who are interested in image processing, image analysis, and computer vision.

<span lang="EN-US">In <span>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.</span></span>