Fangming Bi^{1, 2}, Xuanyi Fu^{1, 2}, Wei Chen^{1, 2, 3, *}, Weidong Fang⁴, Xuzhi Miao^{1, 2}, Biruk Assefa^{1, 5}

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 199-216, 2020, DOI:10.32604/cmc.2020.06258

Abstract Aiming at the defects of the traditional fire detection methods, which are caused by false positives and false negatives in large space buildings, a fire identification detection method based on video images is proposed. The algorithm first uses the hybrid Gaussian background modeling method and the RGB color model to perform fire prejudgment on the video image, which can eliminate most non-fire interferences. Secondly, the traditional regional growth algorithm is improved and the fire image segmentation effect is effectively improved. Then, based on the segmented image, the dynamic and static features of the fire flame 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 >

Zhangyi Shen¹, Feng Ding^{2, *}, Yunqing Shi¹

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 1-16, 2020, DOI:10.32604/cmc.2020.08291

Abstract As a common medium in our daily life, images are important for most people to gather information. There are also people who edit or even tamper images to deliberately deliver false information under different purposes. Thus, in digital forensics, it is necessary to understand the manipulating history of images. That requires to verify all possible manipulations applied to images. Among all the image editing manipulations, recoloring is widely used to adjust or repaint the colors in images. The color information is an important visual information that image can deliver. Thus, it is necessary to guarantee… More >

KRISHAN KUMAR PATEL, RAJESH PUROHIT

Journal of Polymer Materials, Vol.36, No.1, pp. 23-37, 2019, DOI:10.32381/JPM.2019.36.01.3

Abstract Microwave (MV)-induced thermo-responsive shape memory thermoplastic polyurethane (SMTPU)/ MWCNT composites were prepared in micro-compounder. Composites containing different amount of multiwall Carbon nanotube (MWCNT) varying from 0 to 1.5 phr in SMTPU matrix were prepared. Maximum stretching strength, recovery force and tensile strength for 1.5 CNTPU (1.5 phr MWCNT in SMTPU matrix) was increased by 120%, 100% and 24% respectively as compared to SMTPU. MV-induced shape memory is a novel approach for fast, clean and remote heating during operation. MWCNT is strong absorber of microwave irradiation so that SMTPU/ MWCNTs nanocomposites successfully triggered by microwave. More >

Safa Ridene¹ , Reda Yaagoubi¹, Imane Sebari¹, Audrey Alajouanine²

Revue Internationale de Géomatique, Vol.29, No.3, pp. 241-253, 2019, DOI:10.3166/rig.2019.00091

Abstract While shadow can give useful information about size and shape of objects, it can pose problems in feature detection and object detection, thereby, it represents one of the major perturbator phenomenons frequently occurring on images and unfortunately, it is inevitable. “Shadows may lead to the failure of image analysis processes and also cause a poor quality of information which in turn leads to problems in implementation of algorithms.” (Mahajan and Bajpayee, 2015). It also affects multiple image analysis applications, whereby shadow cast by buildings deteriorate the spectral values of the surfaces. Therefore, its presence causes More >

R. Coriat

Oncologie, Vol.21, No.2, pp. 75-81, 2019, DOI:10.3166/onco-2019-0046

Abstract Les tumeurs neuroendocrines pancréatiques (TNEp) sont des tumeurs développées aux dépens du pancréas et nécessitent un bilan diagnostique spécifique. Le bilan d’imagerie d’une TNEp est utile pour le diagnostic ainsi que pour le traitement chirurgical/médical. Récemment, un certain nombre de progrès ont été réalisés dans le domaine de l’imagerie des TNEp, en particulier en ce qui concerne l’imagerie fonctionnelle utilisant des analogues de la somatostatine radiomarqués. Dans cette mise au point, nous abordons les progrès diagnostiques en nous focalisant sur les avancées des derniè- res années. Ainsi, il est abordé l’intérêt de l’imagerie conventionnelle (scanner, More >

Ahmet Elbir^1,∗, Hamza Osman Ilhan¹, Nizamettin Aydin¹

Computer Systems Science and Engineering, Vol.34, No.2, pp. 101-107, 2019, DOI:10.32604/csse.2019.34.101

Abstract The performances of the multivariate techniques are directly related to the variable selection process, which is time consuming and requires resources for testing each possible parameter to achieve the best results. Therefore, optimization methods for variable selection process have been proposed in the literature to find the optimal solution in short time by using less system resources. Contrast enhancement is the one of the most important and the parameter dependent image enhancement technique. In this study, two optimization methods are employed for the variable selection for the contrast enhancement technique. Particle swarm optimization (PSO) and More >

Mohammad Behrouzian Nejad¹, Mohammad Ebrahim Shiri^1,2,*

Computer Systems Science and Engineering, Vol.34, No.2, pp. 91-100, 2019, DOI:10.32604/csse.2019.34.091

Abstract In this paper we propose a new image classification technique. According to this note that most research focuses on extraction of features in the frequency domain, location, and reduction of feature dimensions, in this research we focused on learning step in image classification. The main aim is to use the heuristic methods to increase the function of the estimator of the learning algorithm and continue to achieve the desired state, as well as categorization without user interference and automatically performed by the model produced from the above steps. So, in this paper, a new learning… More >

N. Mohanapriya¹, Dr. B. Kalaavathi²

Intelligent Automation & Soft Computing, Vol.25, No.4, pp. 663-672, 2019, DOI:10.31209/2018.100000041

Abstract Medical images are obtained straight from the medical acquisition devices so that, the image quality becomes poor and may contain noises. Low contrast and poor quality are the major issues in the production of medical images. Medical imaging enhancement technology gives way to solve these issues; it helps the doctors to see the interior portions of the body for early diagnosis, also it improves the features the visual aspects of an image for a right diagnosis. This paper proposes a new blend of Particle Swarm Optimization (PSO) and Accelerated Particle Swarm Optimization (APSO) called Hybrid… More >

S. Deivalakshmi^*, P. Palanisamy¹, X. Z. Gao²

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 459-471, 2019, DOI:10.31209/2018.100000001

Abstract The main aim of this paper is to propose a new technique for enhancing the contrast of dark images using Dynamic Stochastic Resonance (DSR) and Multi Wavelet Transform (MWT), which is computationally more efficient than the conventional methods. In the work, for enhancing the contrast of dark images, the intrinsic noise (darkness) of dark images has been used. The proposed MWT-based DSR scheme (MWT-DSR) can yield better performances in terms of visual information and color preservation than already reported techniques. The desired output response is validated by the Relative Contrast Enhancement Factor (F), Perceptual Quality More >