Sarah M. Alhammad¹, Doaa Sami Khafaga^1,*, Aya Y. Hamed², Osama El-Koumy³, Ehab R. Mohamed³, Khalid M. Hosny³

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2939-2952, 2023, DOI:10.32604/csse.2023.041011 - 09 November 2023

Abstract Face mask detection has several applications, including real-time surveillance, biometrics, etc. Identifying face masks is also helpful for crowd control and ensuring people wear them publicly. With monitoring personnel, it is impossible to ensure that people wear face masks; automated systems are a much superior option for face mask detection and monitoring. This paper introduces a simple and efficient approach for masked face detection. The architecture of the proposed approach is very straightforward; it combines deep learning and local binary patterns to extract features and classify them as masked or unmasked. The proposed system requires… More >

Mona Jamjoom¹, Ahmed Elhadad², Hussein Abulkasim^3,*, Safia Abbas⁴

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 367-382, 2023, DOI:10.32604/cmc.2023.037310 - 08 June 2023

Abstract Several pests feed on leaves, stems, bases, and the entire plant, causing plant illnesses. As a result, it is vital to identify and eliminate the disease before causing any damage to plants. Manually detecting plant disease and treating it is pretty challenging in this period. Image processing is employed to detect plant disease since it requires much effort and an extended processing period. The main goal of this study is to discover the disease that affects the plants by creating an image processing system that can recognize and classify four different forms of plant diseases, More >

Zahraa Tarek¹, Samaa M. Shohieb^1,*, Abdelghafar M. Elhady², El-Sayed M. El-kenawy³, Mahmoud Y. Shams⁴

Computer Systems Science and Engineering, Vol.45, No.3, pp. 3195-3213, 2023, DOI:10.32604/csse.2023.034092 - 21 December 2022

Abstract The ability to detect and localize the human eye is critical for use in security applications and human identification and verification systems. This is because eye recognition algorithms have multiple challenges, such as multi-pose variations, ocular parts, and illumination. Moreover, the modern security applications fail to detect facial expressions from eye images. In this paper, a Speeded-Up Roust Feature (SURF) Algorithm was utilized to localize the face images of the enrolled subjects. We highlighted on eye and pupil parts to be detected based on SURF, Hough Circle Transform (HCT), and Local Binary Pattern (LBP). Afterward,… More >

Yassir Edrees Almalki¹, Maida Khalid², Sharifa Khalid Alduraibi³, Qudsia Yousaf², Maryam Zaffar², Shoayea Mohessen Almutiri⁴, Muhammad Irfan⁵, Mohammad Abd Alkhalik Basha⁶, Alaa Khalid Alduraibi³, Abdulrahman Manaa Alamri⁷, Khalaf Alshamrani⁸, Hassan A. Alshamrani^8,*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4103-4121, 2022, DOI:10.32604/cmc.2022.029039 - 16 June 2022

Abstract Since reporting cases of breast cancer are on the rise all over the world. Especially in regions such as Pakistan, Saudi Arabia, and the United States. Efficient methods for the early detection and diagnosis of breast cancer are needed. The usual diagnosis procedures followed by physicians has been updated with modern diagnostic approaches that include computer-aided support for better accuracy. Machine learning based practices has increased the accuracy and efficiency of medical diagnosis, which has helped save lives of many patients. There is much research in the field of medical imaging diagnostics that can be… More >

Naglaa F. El Abady^1,*, Mohamed Taha¹, Hala H. Zayed^1,2

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1417-1436, 2022, DOI:10.32604/cmc.2022.028044 - 18 May 2022

Abstract Because of the widespread availability of low-cost printers and scanners, document forgery has become extremely popular. Watermarks or signatures are used to protect important papers such as certificates, passports, and identification cards. Identifying the origins of printed documents is helpful for criminal investigations and also for authenticating digital versions of a document in today’s world. Source printer identification (SPI) has become increasingly popular for identifying frauds in printed documents. This paper provides a proposed algorithm for identifying the source printer and categorizing the questioned document into one of the printer classes. A dataset of 1200… More >

Chunhua Pan^1,*, Yi Cao², Jinglong Ren³

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1081-1091, 2022, DOI:10.32604/iasc.2022.028763 - 03 May 2022

Abstract Thangka is a unique painting art form in Tibetan culture. As Thangka was awarded as the first batch of national intangible cultural heritage, it has been brought into focus. Unfortunately, illegal merchants sell fake Thangkas at high prices for profit. Therefore, identifying hand-painted Thangkas from machine-printed fake Thangkas is important for protecting national intangible cultural heritage. The paper uses Content-Based Image Retrieval (CBIR) techniques to analyze the color, shape, texture, and other characteristics of hand-painted and machine- printed Thangka images, in order to identify Thangkas. Based on the database collected and established by this project… More >

V. Manimaran^*, K. G. Srinivasagan

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1109-1121, 2022, DOI:10.32604/iasc.2022.023145 - 03 May 2022

Abstract Individual re-identification proof (Re-ID) targets recovering an individual of interest across different non-covering cameras. With the recent development of technological algorithm and expanding request of intelligence video observation, it has acquired fundamentally expanded interest in the computer vision. Person re-identification is characterized as the issue of perceiving an individual caught in different occasions and additionally areas more than a few nonoverlapping camera sees, thinking about a huge arrangement of up-and-comers. This issue influences essentially the administration of disseminated, multiview observation frameworks, in which subjects should be followed across better places, either deduced or on-the-fly when… More >

Saeed Iqbal^1,*, Adnan N. Qureshi¹, Ghulam Mustafa²

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4915-4939, 2022, DOI:10.32604/cmc.2022.023178 - 14 January 2022

Abstract Skin cancer (melanoma) is one of the most aggressive of the cancers and the prevalence has significantly increased due to increased exposure to ultraviolet radiation. Therefore, timely detection and management of the lesion is a critical consideration in order to improve lifestyle and reduce mortality. To this end, we have designed, implemented and analyzed a hybrid approach entailing convolutional neural networks (CNN) and local binary patterns (LBP). The experiments have been performed on publicly accessible datasets ISIC 2017, 2018 and 2019 (HAM10000) with data augmentation for in-distribution generalization. As a novel contribution, the CNN architecture More >

S. Beatrice^*, Janaki Meena

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 331-347, 2022, DOI:10.32604/iasc.2022.023666 - 05 January 2022

Abstract Discovering the information about several disorders prevailing in brain and neurology is by no means a new scientific technique. A neurological disorder of any human being can be analyzed using EEG (Electroencephalography) signal from the electrode’s output. Epilepsy (spontaneous recurrent seizure) detection is usually carried out by the physicians using a visual scanning of the signals produced by EEG, which is onerous and may be inaccurate. EEG signal is often used to determine epilepsy, for its merits, such as non-invasive, portable, and economical, can exhibit superior temporal tenacity. This paper surveys the existing artifact removal… More >

Razi J. Al-Azawi¹, Nadia M. G. Al-Saidi², Hamid A. Jalab^3,*, Rabha W. Ibrahim⁴, Dumitru Baleanu^5,6,7

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3903-3915, 2021, DOI:10.32604/cmc.2021.020368 - 24 August 2021

Abstract Over the past years, image manipulation tools have become widely accessible and easier to use, which made the issue of image tampering far more severe. As a direct result to the development of sophisticated image-editing applications, it has become near impossible to recognize tampered images with naked eyes. Thus, to overcome this issue, computer techniques and algorithms have been developed to help with the identification of tampered images. Research on detection of tampered images still carries great challenges. In the present study, we particularly focus on image splicing forgery, a type of manipulation where a… More >