Dongjie Liu¹, Jin Zhao^{1, *}, Axin Xi², Chao Wang¹, Xinnian Huang¹, Kuncheng Lai¹, Chang Liu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 593-617, 2020, DOI:10.32604/cmes.2020.08641

Abstract With the advent of deep learning, self-driving schemes based on deep learning are becoming more and more popular. Robust perception-action models should learn from data with different scenarios and real behaviors, while current end-to-end model learning is generally limited to training of massive data, innovation of deep network architecture, and learning in-situ model in a simulation environment. Therefore, we introduce a new image style transfer method into data augmentation, and improve the diversity of limited data by changing the texture, contrast ratio and color of the image, and then it is extended to the scenarios that the model has been… More >

Mengling Zou¹, Zhengxuan Liu², Xianyi Chen^{3, *}

Journal on Big Data, Vol.1, No.3, pp. 151-158, 2019, DOI:10.32604/jbd.2019.09057

Abstract Image encryption (IE) is a very useful and popular technology to protect the privacy of users. Most algorithms usually encrypt the original image into an image similar to texture or noise, but texture and noise are an obvious visual indication that the image has been encrypted, which is more likely to cause the attacks of enemy. To overcome this shortcoming, many image encryption systems, which convert the original image into a carrier image with visual significance have been proposed. However, the generated cryptographic image still has texture features. In line with the idea of improving the visual quality of the… More >

Xuyu Xiang¹, Jiaohua Qin^{1, *}, Junshan Tan¹, Neal N. Xiong¹

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 963-976, 2020, DOI:10.32604/cmc.2020.06394

Abstract In this paper, a new adaptive calibration algorithm for image steganalysis is proposed. Steganography disturbs the dependence between neighboring pixels and decreases the neighborhood node degree. Firstly, we analyzed the effect of steganography on the neighborhood node degree of cover images. Then, the calibratable pixels are marked by the analysis of neighborhood node degree. Finally, the strong correlation calibration image is constructed by revising the calibratable pixels. Experimental results reveal that compared with secondary steganography the image calibration method significantly increased the detection accuracy for LSB matching steganography on low embedding ratio. The proposed method also has a better performance… More >

N. Shobha Rani^{1, *}, M. Chandrajith², B. R. Pushpa¹, B. J. Bipin Nair¹

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 679-694, 2020, DOI:10.32604/cmc.2020.08552

Abstract Assessing the age of an individual via bones serves as a fool proof method in true determination of individual skills. Several attempts are reported in the past for assessment of chronological age of an individual based on variety of discriminative features found in wrist radiograph images. The permutation and combination of these features realized satisfactory accuracies for a set of limited groups. In this paper, assessment of gender for individuals of chronological age between 1-17 years is performed using left hand wrist radiograph images. A fully automated approach is proposed for removal of noise persisted due to non-uniform illumination during… More >

Noor Mualla¹, Essam H Houssein^{2, *}, M. R. Hassan¹

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 591-605, 2020, DOI:10.32604/cmc.2020.08580

Abstract Chronological age estimation using panoramic dental X-ray images is an essential task in forensic sciences. Various statistical approaches have proposed by considering the teeth and mandible. However, building automated dental age estimation based on machine learning techniques needs more research efforts. In this paper, an automated dental age estimation is proposed using transfer learning. In the proposed approach, features are extracted using two deep neural networks namely, AlexNet and ResNet. Several classifiers are proposed to perform the classification task including decision tree, k-nearest neighbor, linear discriminant, and support vector machine. The proposed approach is evaluated using a number of suitable… More >

Satya Prakash Yadav^{1, *}, Sachin Yadav²

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 303-321, 2020, DOI:10.32604/cmes.2020.08459

Abstract This paper presents a low intricate, profoundly energy effective MRI Images combination intended for remote visual sensor frameworks which leads to improved understanding and implementation of treatment; especially for radiology. This is done by combining the original picture which leads to a significant reduction in the computation time and frequency. The proposed technique conquers the calculation and energy impediment of low power tools and is examined as far as picture quality and energy is concerned. Reenactments are performed utilizing MATLAB 2018a, to quantify the resultant vitality investment funds and the reproduction results show that the proposed calculation is very quick… More >

Sahib Khan^{1, *}, Arslan Arif¹, Syed Tahir Hussain Rizvi², Nasir Ahmad³

CMES-Computer Modeling in Engineering & Sciences, Vol.117, No.1, pp. 1-16, 2018, DOI:10.31614/cmes.2018.04141

Abstract Cryptography and steganography are two important and related fields of infor- mation security. But, steganography is slightly different in the sense that it hides the ex- istence of secret information from unauthorized users. It is one of the most appealing research domains, have applications like copyright protection, data integrity protection and manipulation detection. Several steganography techniques have been proposed in literature. But, in this work a new information hiding algorithm is presented. The proposed technique de-correlates frequency components of cover image using discrete cosine transform and uses the least significant bits of frequency components for hiding secret information. The tech-nique… More >

Hee-Jin Yoon¹, Kang-Jik Kim¹, Jun-Chul Chun^1,*

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 459-472, 2020, DOI:10.32604/cmc.2020.08799

Abstract Recently, virtual reality technology that can interact with various data is used for urban design and analysis. Reality, one of the most important elements in virtual reality technology, means visual expression so that a person can experience threedimensional space like reality. To obtain this realism, real-world data are used in the various fields. For example, in order to increase the realism of 3D modeled building textures real aerial images are utilized in 3D modelling. However, the aerial image captured during the day can be shadowed by the sun and it can cause the distortion or deterioration of image. To resolve… More >

Gang Xu^{1, *}, Ran Ling¹, Lishan Deng¹, Qing Wu¹, Weiyin Ma²

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 309-319, 2020, DOI:10.32604/cmc.2020.06509

Abstract In this paper, we propose a novel image interpolation method by using Gaussian-Sinc automatic interpolators with partition of unity property. A comprehensive comparison is made with classical image interpolation methods, such as the bicubic interpolation, Lanczos interpolation, cubic Schaum interpolation, cubic B-spline interpolation and cubic Moms interpolation. The experimental results show the effectiveness of the improved image interpolation method via some image quality metrics such as PSNR and SSIM. More >

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 are further analyzed and extracted… More >