A novel comprehensive database for arabic and english off-line handwritten digits recognition

Abstract

<span>The recognition of Arabic handwritten is received at the same interest as other Latin languages. In Optical Character Recognition (OCR), handwriting Arabic recognition is considered as one of the critical and difficult tasks in the various scientific area. The main issues of this matter were due to the lack of public Arabic handwriting databases and the cursive nature of Arabic writing. In this paper, a new benchmark database is built for the Arabic and English off-line handwritten digits Recognition. The original form is divided into three groups: Arabic digits, English digits, and word Arabic digits which written five times by 100 different academic staff and students of university writers. Our database contains 14500 images; divided into two subsets of training and testing to help researchers through evaluating and comparing results obtained from their systems. </span>

A cloud computing scheduling and its evolutionary approaches

“…Table 1 illustrated the advantage and disadvantage of algorithms that which were mentioned and Figure 2 shows the types of scheduling algorithms. On the other hand, the pattern recognition is an important and fertile topic as it has entered many applications such as recognizing the different languages from Arabic, English, and other languages of the world [39], so, many databases have been built to implement and test these applications [40][41][42][43][44], as result, the recognition has entered a large area in many applications in the cloud environment such as Emotion of human [45] and activity recognition [46], and face recognition [47][48][49]. Easier for implementing, and it is free from famine (which means that the process does not have the resources to complete it permanently or after a long time.…”

A Feature Extraction Method for Arabic Offline Handwritten Recognition System Using Naïve Bayes Classifier

“…The second and also the third systems were built based on two blocks: pre-processing methodology and statistical, structural, and features of topological that extracted from the main and secondary characters, this system used ANN, KNN, SVM classifiers in two and three systems respectively. Recently some studies focused on creating Arabic Offline Handwritten databases for evaluating and matching results [14] [15] [16].…”