Peng Chen¹, Weiwei Zhang^1,*, Ziyao Xiao¹, Yongxiang Tian²

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 97-109, 2022, DOI:10.32604/cmes.2022.016632

Abstract Road accident detection plays an important role in abnormal scene reconstruction for Intelligent Transportation Systems and abnormal events warning for autonomous driving. This paper presents a novel 3D object detector and adaptive space partitioning algorithm to infer traffic accidents quantitatively. Using 2D region proposals in an RGB image, this method generates deformable frustums based on point cloud for each 2D region proposal and then frustum-wisely extracts features based on the farthest point sampling network (FPS-Net) and feature extraction network (FE-Net). Subsequently, the encoder-decoder network (ED-Net) implements 3D-oriented bounding box (OBB) regression. Meanwhile, the adaptive least square regression (ALSR) method is… More >

Hengyang Wang, Jin Liu^*, Haoliang Ren

Journal on Big Data, Vol.3, No.3, pp. 119-126, 2021, DOI:10.32604/jbd.2021.017184

Abstract The past decade has seen the rapid development of text detection based on deep learning. However, current methods of Chinese character detection and recognition have proven to be poor. The accuracy of segmenting text boxes in natural scenes is not impressive. The reasons for this strait can be summarized into two points: the complexity of natural scenes and numerous types of Chinese characters. In response to these problems, we proposed a lightweight neural network architecture named CTSF. It consists of two modules, one is a text detection network that combines CTPN and the image feature extraction modules of PVANet, named… More >

Shumukh M. Aljuaid^*, Arshiya S. Ansari

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1009-1025, 2022, DOI:10.32604/csse.2022.020785

Abstract This paper presents a novel method of a secured card-less Automated Teller Machine (ATM) authentication based on the three bio-metrics measures. It would help in the identification and authorization of individuals and would provide robust security enhancement. Moreover, it would assist in providing identification in ways that cannot be impersonated. To the best of our knowledge, this method of Biometric_ fusion way is the first ATM security algorithm that utilizes a fusion of three biometric features of an individual such as Fingerprint, Face, and Retina simultaneously for recognition and authentication. These biometric images have been collected as input data for… More >

Usman Ali, Muhammad Tariq Mahmood^*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1597-1611, 2022, DOI:10.32604/cmc.2022.022219

Abstract Enormous methods have been proposed for the detection and segmentation of blur and non-blur regions of the images. Due to the limited available information about blur type, scenario and the level of blurriness, detection and segmentation is a challenging task. Hence, the performance of the blur measure operator is an essential factor and needs improvement to attain perfection. In this paper, we propose an effective blur measure based on local binary pattern (LBP) with adaptive threshold for blur detection. The sharpness metric developed based on LBP used a fixed threshold irrespective of the type and level of blur, that may… More >

P. Prabu¹, K. Venkatachalam², Ala Saleh Alluhaidan^3,*, Radwa Marzouk⁴, Myriam Hadjouni⁵, Sahar A. El_Rahman^5,6

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1133-1152, 2022, DOI:10.32604/cmc.2022.020919

Abstract COVID’19 has caused the entire universe to be in existential health crisis by spreading globally in the year 2020. The lungs infection is detected in Computed Tomography (CT) images which provide the best way to increase the existing healthcare schemes in preventing the deadly virus. Nevertheless, separating the infected areas in CT images faces various issues such as low-intensity difference among normal and infectious tissue and high changes in the characteristics of the infection. To resolve these issues, a new inf-Net (Lung Infection Segmentation Deep Network) is designed for detecting the affected areas from the CT images automatically. For the… More >

T. Jeslin^1,*, J. Arul Linsely²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 171-182, 2022, DOI:10.32604/cmc.2022.020255

Abstract Brain cancer is the premier reason for cancer deaths all over the world. The diagnosis of brain cancer at an initial stage is mediocre, as the radiologist is ineffectual. Different experiments have been conducted and demonstrated clearly that the algorithms for nodule segmentation are unsuccessful. Therefore, the research has consolidated incremental clustering focused on superpixel segmentation as an appropriate optimization approach for the accurate segmentation of pulmonary nodules. The key aim of the research is to refine brain CT images to accurately distinguish tumors and the segmentation of small-scale anomalous nodules in the brain region. In the beginning stage, an… More >

Fuchu Zhang¹, Yanpeng Wu^2,*, Miaoqing Xu², Sanjun Liu³, Changling Peng², Zhichen Gao⁴

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 301-321, 2022, DOI:10.32604/iasc.2022.021929

Abstract Cell segmentation is an important topic in medicine. A cell image segmentation algorithm based on morphology is proposed. First, some morphological operations, including top-hat transformation, bot-hat transformation, erosion operation, dilation operation, opening operation, closing operation, majority operation, skeleton operation, etc., are applied to remove noise or enhance cell images. Then the small blocks in the cell image are deleted as noise, the medium blocks are removed and saved as normal cells, and the large blocks are segmented as overlapping cells. Each point on the edge of the overlapping cell area to be divided is careful checked. If the shape of… More >

R. Rajaragavi^1,*, S. Palanivel Rajan²

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 1-14, 2022, DOI:10.32604/iasc.2022.021206

Abstract A brain tumor is a portion of uneven cells, need to be detected earlier for treatment. Magnetic Resonance Imaging (MRI) is a routinely utilized procedure to take brain tumor images. Manual segmentation of tumor is a crucial task and laborious. There is a need for an automated system for segmentation and classification for tumor surgery and medical treatments. This work suggests an efficient brain tumor segmentation and classification based on deep learning techniques. Initially, Squirrel search optimized bidirectional ConvLSTM U-net with attention gate proposed for brain tumour segmentation. Then, the Hybrid Deep ResNet and Inception Model used for classification. Squirrel… More >

Sagheer Abbas¹, Yousef Alhwaiti², Areej Fatima³, Muhammad A. Khan⁴, Muhammad Adnan Khan^5,*, Taher M. Ghazal^6,7, Asma Kanwal^1,8, Munir Ahmad¹, Nouh Sabri Elmitwally^2,9

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4563-4581, 2022, DOI:10.32604/cmc.2022.021102

Abstract This paper presents a handwritten document recognition system based on the convolutional neural network technique. In today’s world, handwritten document recognition is rapidly attaining the attention of researchers due to its promising behavior as assisting technology for visually impaired users. This technology is also helpful for the automatic data entry system. In the proposed system prepared a dataset of English language handwritten character images. The proposed system has been trained for the large set of sample data and tested on the sample images of user-defined handwritten documents. In this research, multiple experiments get very worthy recognition results. The proposed system… More >

Mohamed Yacin Sikkandar^1,*, S. Sabarunisha Begum², Abdulaziz A. Alkathiry³, Mashhor Shlwan N. Alotaibi¹, Md Dilsad Manzar⁴

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4279-4291, 2022, DOI:10.32604/cmc.2022.020571

Abstract Knee Osteoarthritis (KOA) is a degenerative knee joint disease caused by ‘wear and tear’ of ligaments between the femur and tibial bones. Clinically, KOA is classified into four grades ranging from 1 to 4 based on the degradation of the ligament in between these two bones and causes suffering from impaired movement. Identifying this space between bones through the anterior view of a knee X-ray image is solely subjective and challenging. Automatic classification of this process helps in the selection of suitable treatment processes and customized knee implants. In this research, a new automatic classification of KOA images based on… More >