Mohamed Amin Ben Atitallah^1,2,3,*, Rostom Kachouri², Ahmed Ben Atitallah⁴, Hassene Mnif¹

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5963-5977, 2022, DOI:10.32604/cmc.2022.024345

Abstract In the context of constructing an embedded system to help visually impaired people to interpret text, in this paper, an efficient High-level synthesis (HLS) Hardware/Software (HW/SW) design for text extraction using the Gamma Correction Method (GCM) is proposed. Indeed, the GCM is a common method used to extract text from a complex color image and video. The purpose of this work is to study the complexity of the GCM method on Xilinx ZCU102 FPGA board and to propose a HW implementation as Intellectual Property (IP) block of the critical blocks in this method using HLS flow with taking account the… More >

Amira Baumy¹, Abeer D. Algarni^2,*, Mahmoud Abdalla³, Walid El-Shafai^4,5, Fathi E. Abd El-Samie^3,4, Naglaa F. Soliman^2,3

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3257-3276, 2022, DOI:10.32604/cmc.2022.021047

Abstract This paper is concerned with a vital topic in image processing: color image forgery detection. The development of computing capabilities has led to a breakthrough in hacking and forgery attacks on signal, image, and data communicated over networks. Hence, there is an urgent need for developing efficient image forgery detection algorithms. Two main types of forgery are considered in this paper: splicing and copy-move. Splicing is performed by inserting a part of an image into another image. On the other hand, copy-move forgery is performed by copying a part of the image into another position in the same image. The… More >

V. Thanikachalam^1,*, S. Shanthi², K. Kalirajan³, Sayed Abdel-Khalek^4,5, Mohamed Omri⁶, Lotfi M. Ladhar⁷

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5667-5681, 2022, DOI:10.32604/cmc.2022.020965

Abstract The rapid development of biomedical imaging modalities led to its wide application in disease diagnosis. Tongue-based diagnostic procedures are proficient and non-invasive in nature to carry out secondary diagnostic processes ubiquitously. Traditionally, physicians examine the characteristics of tongue prior to decision-making. In this scenario, to get rid of qualitative aspects, tongue images can be quantitatively inspected for which a new disease diagnosis model is proposed. This model can reduce the physical harm made to the patients. Several tongue image analytical methodologies have been proposed earlier. However, there is a need exists to design an intelligent Deep Learning (DL) based disease… More >

Muhammad Alyas Khan¹, Mushtaq Ali¹, Mohsin Shah², Toqeer Mahmood³, Muneer Ahmad⁴, NZ Jhanjhi⁵, Mohammad Arif Sobhan Bhuiyan^6,*, Emad Sami Jaha⁷

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 771-785, 2021, DOI:10.32604/iasc.2021.018039

Abstract Fungi disease affects walnut trees worldwide because it damages the canopies of the trees and can easily spread to neighboring trees, resulting in low quality and less yield. The fungal disease can be treated relatively easily, and the main goal is preventing its spread by automatic early-detection systems. Recently, machine learning techniques have achieved promising results in many applications in the agricultural field, including plant disease detection. In this paper, an automatic machine learning-based detection method for identifying walnut diseases is proposed. The proposed method first resizes a leaf’s input image and pre-processes it using intensity adjustment and histogram equalization.… More >

Lord Amoah^1,2,*, Ampofo Twumasi Kwabena³

Journal of Quantum Computing, Vol.3, No.2, pp. 65-77, 2021, DOI:10.32604/jqc.2021.020734

Abstract Recent contrast enhancement (CE) methods, with a few exceptions, predominantly focus on enhancing gray-scale images. This paper proposes a bihistogram shifting contrast enhancement for color images based on the RGB (red, green, and blue) color model. The proposed method selects the two highest bins and two lowest bins from the image histogram, performs an equalized number of bidirectional histogram shifting repetitions on each RGB channel while embedding secret data into marked images. The proposed method simultaneously performs both right histogram shifting (RHS) and left histogram shifting (LHS) in each histogram shifting repetition to embed and split the highest bins while… More >

Turki M. Alanazi¹, Ahmed Ben Atitallah^1,2,*, Imen Abid²

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2925-2943, 2021, DOI:10.32604/cmc.2021.017575

Abstract In this paper, a software/hardware High-level Synthesis (HLS) design is proposed to compute the Adaptive Vector Median Filter (AVMF) in real-time. In fact, this filter is known by its excellent impulsive noise suppression and chromaticity conservation. The software (SW) study of this filter demonstrates that its implementation is too complex. The purpose of this work is to study the impact of using an HLS tool to design ideal floating-point and optimized fixed-point hardware (HW) architectures for the AVMF filter using square root function (ideal HW) and ROM memory (optimized HW), respectively, to select the best HLS architectures and to design… More >

Nazli Sanam^1,*, Asif Ali¹, Tariq Shah¹, Ghazanfar Farooq²

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1-21, 2021, DOI:10.32604/cmc.2021.014442

Abstract The substitution box (S-box) is a fundamentally important component of symmetric key cryptosystem. An S-box is a primary source of non-linearity in modern block ciphers, and it resists the linear attack. Various approaches have been adopted to construct S-boxes. S-boxes are commonly constructed over commutative and associative algebraic structures including Galois fields, unitary commutative rings and cyclic and non-cyclic finite groups. In this paper, first a non-associative ring of order 512 is obtained by using computational techniques, and then by this ring a triplet of 8 × 8 S-boxes is designed. The motivation behind the designing of these S-boxes is… More >

R.V.V. Krishna^1,*, S. Srinivas Kumar²

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 281-290, 2020, DOI:10.31209/2019.100000121

Abstract In this paper, a color image segmentation algorithm is proposed by extracting both texture and color features and applying them to the one -against-all multi class support vector machine (MSVM) classifier for segmentation. Local Binary Pattern is used for extracting the textural features and L*a*b color model is used for obtaining the color features. The MSVM is trained using the samples obtained from a novel soft rough fuzzy c-means (SRFCM) clustering. The fuzzy set based membership functions capably handle the problem of overlapping clusters. The lower and upper approximation concepts of rough sets deal well with uncertainty, vagueness, and incompleteness… More >

Jinwei Wang^{1, 2, 3, 4}, Qiye Ni³, Yang Zhang³, Xiangyang Luo^{2, *}, Yunqing Shi⁵, Jiangtao Zhai³, Sunil Kr Jha³

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 929-943, 2020, DOI:10.32604/cmc.2020.06569

Abstract Median filtering is a nonlinear signal processing technique and has an advantage in the field of image anti-forensics. Therefore, more attention has been paid to the forensics research of median filtering. In this paper, a median filtering forensics method based on quaternion convolutional neural network (QCNN) is proposed. The median filtering residuals (MFR) are used to preprocess the images. Then the output of MFR is expanded to four channels and used as the input of QCNN. In QCNN, quaternion convolution is designed that can better mix the information of different channels than traditional methods. The quaternion pooling layer is designed… More >

Jinwei Wang^{1, *}, Yang Zhang¹

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 99-112, 2020, DOI:10.32604/cmc.2020.04373

Abstract In the paper, a convolutional neural network based on quaternion transformation is proposed to detect median filtering for color images. Compared with conventional convolutional neural network, color images can be processed in a holistic manner in the proposed scheme, which makes full use of the correlation between RGB channels. And due to the use of convolutional neural network, it can effectively avoid the one-sidedness of artificial features. Experimental results have shown the scheme’s improvement over the state-of-the-art scheme on the accuracy of color image median filtering detection. More >