Arfa Siddiqu, Abdul Basit^*, Waheed Noor, Muhammad Asfandyar Khan, M. Saeed H. Kakar, Azam Khan

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 875-885, 2023, DOI:10.32604/iasc.2023.036426

Abstract The optical character recognition for the right to left and cursive languages such as Arabic is challenging and received little attention from researchers in the past compared to the other Latin languages. Moreover, the absence of a standard publicly available dataset for several low-resource languages, including the Pashto language remained a hurdle in the advancement of language processing. Realizing that, a clean dataset is the fundamental and core requirement of character recognition, this research begins with dataset generation and aims at a system capable of complete language understanding. Keeping in view the complete and full autonomous recognition of the cursive… More >

Xun Zhang¹, Wanrong Bai¹, Haoyang Cui^2,*

Energy Engineering, Vol.120, No.3, pp. 665-679, 2023, DOI:10.32604/ee.2023.020342

Abstract Optical Character Recognition (OCR) refers to a technology that uses image processing technology and character recognition algorithms to identify characters on an image. This paper is a deep study on the recognition effect of OCR based on Artificial Intelligence (AI) algorithms, in which the different AI algorithms for OCR analysis are classified and reviewed. Firstly, the mechanisms and characteristics of artificial neural network-based OCR are summarized. Secondly, this paper explores machine learning-based OCR, and draws the conclusion that the algorithms available for this form of OCR are still in their infancy, with low generalization and fixed recognition errors, albeit with… More >

Moeen Tayyab¹, Ayyaz Hussain^2,*, Usama Mir³, M. Aqeel Iqbal⁴, Muhammad Haneef⁵

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6177-6193, 2023, DOI:10.32604/cmc.2023.034669

Abstract The news ticker is a common feature of many different news networks that display headlines and other information. News ticker recognition applications are highly valuable in e-business and news surveillance for media regulatory authorities. In this paper, we focus on the automatic Arabic Ticker Recognition system for the Al-Ekhbariya news channel. The primary emphasis of this research is on ticker recognition methods and storage schemes. To that end, the research is aimed at character-wise explicit segmentation using a semantic segmentation technique and words identification method. The proposed learning architecture considers the grouping of homogeneous-shaped classes. This incorporates linguistic taxonomy in… More >

Salah Alghyaline^*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 1825-1861, 2023, DOI:10.32604/cmes.2022.024555

Abstract This study aims to review the latest contributions in Arabic Optical Character Recognition (OCR) during the last decade, which helps interested researchers know the existing techniques and extend or adapt them accordingly. The study describes the characteristics of the Arabic language, different types of OCR systems, different stages of the Arabic OCR system, the researcher’s contributions in each step, and the evaluation metrics for OCR. The study reviews the existing datasets for the Arabic OCR and their characteristics. Additionally, this study implemented some preprocessing and segmentation stages of Arabic OCR. The study compares the performance of the existing methods in… More >

D. Suvitha^*, M. Vijayalakshmi

Computer Systems Science and Engineering, Vol.44, No.1, pp. 873-894, 2023, DOI:10.32604/csse.2023.025189

Abstract Recent advancement in low-cost cameras has facilitated surveillance in various developing towns in India. The video obtained from such surveillance are of low quality. Still counting vehicles from such videos are necessity to avoid traffic congestion and allows drivers to plan their routes more precisely. On the other hand, detecting vehicles from such low quality videos are highly challenging with vision based methodologies. In this research a meticulous attempt is made to access low-quality videos to describe traffic in Salem town in India, which is mostly an un-attempted entity by most available sources. In this work profound Detection Transformer (DETR)… More >

Vijaya Krishna Sonthi^1,*, S. Nagarajan¹, N. Krishnaraj²

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1725-1736, 2022, DOI:10.32604/iasc.2022.026940

Abstract In India, Telugu is one of the official languages and it is a native language in the Andhra Pradesh and Telangana states. Although research on Telugu optical character recognition (OCR) began in the early 1970s, it is still necessary to develop effective printed character recognition for the Telugu language. OCR is a technique that aids machines in identifying text. The main intention in the classifier design of the OCR systems is supervised learning where the training process takes place on the labeled dataset with numerous characters. The existing OCR makes use of patterns and correlations to differentiate words from other… More >

Sunil Dhankhar^1,*, Mukesh Kumar Gupta¹, Fida Hussain Memon^2,3, Surbhi Bhatia⁴, Pankaj Dadheech¹, Arwa Mashat⁵

Computer Systems Science and Engineering, Vol.43, No.1, pp. 397-412, 2022, DOI:10.32604/csse.2022.024059

Abstract In today’s digital era, the text may be in form of images. This research aims to deal with the problem by recognizing such text and utilizing the support vector machine (SVM). A lot of work has been done on the English language for handwritten character recognition but very less work on the under-resourced Hindi language. A method is developed for identifying Hindi language characters that use morphology, edge detection, histograms of oriented gradients (HOG), and SVM classes for summary creation. SVM rank employs the summary to extract essential phrases based on paragraph position, phrase position, numerical data, inverted comma, sentence… More >

Samah Ibrahim Alshathri^1,*, Desiree Juby Vincent², V. S. Hari²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1371-1386, 2022, DOI:10.32604/cmc.2022.022458

Abstract Invoice document digitization is crucial for efficient management in industries. The scanned invoice image is often noisy due to various reasons. This affects the OCR (optical character recognition) detection accuracy. In this paper, letter data obtained from images of invoices are denoised using a modified autoencoder based deep learning method. A stacked denoising autoencoder (SDAE) is implemented with two hidden layers each in encoder network and decoder network. In order to capture the most salient features of training samples, a undercomplete autoencoder is designed with non-linear encoder and decoder function. This autoencoder is regularized for denoising application using a combined… More >

Ishaani Priyadarshini^*, Chase Cotton

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 781-800, 2022, DOI:10.32604/cmc.2022.019284

Abstract

The increasing capabilities of Artificial Intelligence (AI), has led researchers and visionaries to think in the direction of machines outperforming humans by gaining intelligence equal to or greater than humans, which may not always have a positive impact on the society. AI gone rogue, and Technological Singularity are major concerns in academia as well as the industry. It is necessary to identify the limitations of machines and analyze their incompetence, which could draw a line between human and machine intelligence. Internet memes are an amalgam of pictures, videos, underlying messages, ideas, sentiments, humor, and experiences, hence the way an internet… More >