Ranu Gupta^1,3,*, Rahul Pachauri^2,3, Ashutosh Kumar Singh^1,4

Molecular & Cellular Biomechanics, Vol.15, No.2, pp. 63-83, 2018, DOI: 10.3970/mcb.2018.00114

Abstract Various chaos-based image encryption schemes have been proposed in last few years. The proposed image encryption method uses chaotic map. The encryption is done by using 256 bit long external secret key. The initial condition for the chaotic mapping is evaluated by the use of external secret key along with the mapping function. Besides that, the proposed method is made more robust by applying multiple operations to the pixels of the image depending on the outcome of the calculation of the logistic map. Moreover, block shuffling of the image and modifying the secret key after encryption of each row is… More >

Yongjie Zhang^∗, Yiming Jing^∗, Xinghua Liang^∗, Guoliang Xu^†, Lei Dong^‡

Molecular & Cellular Biomechanics, Vol.9, No.3, pp. 213-226, 2012, DOI:10.3970/mcb.2012.009.213

Abstract A greyscale-based fully automatic deformable image registration algorithm, based on an optical flow method together with geometric smoothing, is developed for dynamic lung modeling and tumor tracking. In our computational processing pipeline, the input data is a set of 4D CT images with 10 phases. The triangle mesh of the lung model is directly extracted from the more stable exhale phase (Phase 5). In addition, we represent the lung surface model in 3D volumetric format by applying a signed distance function and then generate tetrahedral meshes. Our registration algorithm works for both triangle and tetrahedral meshes. In CT images, the… More >

Hao Wu¹, Qi Liu^{2, 3, *}, Xiaodong Liu⁴

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 575-597, 2019, DOI:10.32604/cmc.2019.03595

Abstract Deep learning technology has brought great impetus to artificial intelligence, especially in the fields of image processing, pattern and object recognition in recent years. Present proposed artificial neural networks and optimization skills have effectively achieved large-scale deep learnt neural networks showing better performance with deeper depth and wider width of networks. With the efforts in the present deep learning approaches, factors, e.g., network structures, training methods and training data sets are playing critical roles in improving the performance of networks. In this paper, deep learning models in recent years are summarized and compared with detailed discussion of several typical networks… More >

Maoyang Zou^1,2, Jinrong Hu², Huan Zhang², Xi Wu², Jia He², Zhijie Xu³, Yong Zhong^1,*

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 511-525, 2019, DOI:10.32604/cmc.2019.05912

Abstract For image-guided radiation therapy, radiosurgery, minimally invasive surgery, endoscopy and interventional radiology, one of the important techniques is medical image registration. In our study, we propose a learning-based approach named “FIP-CNNF” for rigid registration of medical image. Firstly, the pixel-level interest points are computed by the full convolution network (FCN) with self-supervise. Secondly, feature detection, descriptor and matching are trained by convolution neural network (CNN). Thirdly, random sample consensus (Ransac) is used to filter outliers, and the transformation parameters are found with the most inliers by iteratively fitting transforms. In addition, we propose “TrFIP-CNNF” which uses transfer learning and fine-tuning… More >

Shaojiang Zhong^{1, *}

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 465-479, 2019, DOI:10.32604/cmc.2019.05853

Abstract Based on the three-dimensional classic Chua circuit, a nonlinear circuit containing two flux-control memristors is designed. Due to the difference in the design of the characteristic equation of the two magnetron memristors, their position form a symmetrical structure with respect to the capacitor. The existence of chaotic properties is proved by analyzing the stability of the system, including Lyapunov exponent, equilibrium point, eigenvalue, Poincare map, power spectrum, bifurcation diagram et al. Theoretical analysis and numerical calculation show that this heterogeneous memristive model is a hyperchaotic five-dimensional nonlinear dynamical system and has a strong chaotic behavior. Then, the memristive system is… More >

Jiancheng Zou^1,*, Zhengzheng Li¹, Zhijun Guo¹, Don Hong²

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 163-177, 2019, DOI:10.32604/cmc.2019.05795

Abstract In the field of images and imaging, super-resolution (SR) reconstruction of images is a technique that converts one or more low-resolution (LR) images into a highresolution (HR) image. The classical two types of SR methods are mainly based on applying a single image or multiple images captured by a single camera. Microarray camera has the characteristics of small size, multi views, and the possibility of applying to portable devices. It has become a research hotspot in image processing. In this paper, we propose a SR reconstruction of images based on a microarray camera for sharpening and registration processing of array… More >

Xingxing Xiao¹, Yang^1,*, Rui Li², Weiming Zhang³

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 101-115, 2019, DOI:10.32604/cmc.2019.05293

Abstract The medical industry develops rapidly as science and technology advance. People benefit from medical resource sharing, but suffer from privacy leaks at the same time. In order to protect patients’ privacy and improve quality of medical images, a novel reversible data hiding (RDH) scheme based on lesion extraction and with contrast enhancement is proposed. Furthermore, the proposed scheme can enhance the contrast of medial image's lesion area directly and embed high-capacity privacy data reversibly. Different from previous segmentation methods, this scheme first adopts distance regularized level set evolution (DRLSE) to extract lesion and targets at the lesion area accurately for… More >

Jiwei Zhang¹, Yueying Li², Shaozhang Niu^1,*, Zhiyi Cao¹, Xinyi Wang¹

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 287-303, 2019, DOI:10.32604/cmc.2019.05353

Abstract With the rapid development of image editing techniques, the image splicing behavior, typically for those that involve copying a portion from one original image into another targeted image, has become one of the most prevalent challenges in our society. The existing algorithms relying on hand-crafted features can be used to detect image splicing but unfortunately lack precise location information of the tampered region. On the basis of changing the classifications of fully convolutional network (FCN), here we proposed an improved FCN that enables locating the spliced region. Specifically, we first insert the original images into the training dataset that contains… More >

D. Yuvaraj¹, M. Sivaram², B. Karthikeyan^3,*, Jihan Abdulazeez⁴

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 729-739, 2019, DOI:10.32604/cmc.2019.05945

Abstract The perfect image retrieval and retrieval time are the two major challenges in CBIR systems. To improve the retrieval accuracy, the whole database is searched based on many image characteristics such as color, shape, texture and edge information which leads to more time consumption. This paper presents a new fuzzy based CBIR method, which utilizes colour, shape and texture attributes of the image. Fuzzy rule based system is developed by combining color, shape, and texture feature for enhanced image recovery. In this approach, DWT is used to pull out the texture characteristics and the region based moment invariant is utilized… More >

Lina Shi¹, Zichi Wang¹, Zhenxing Qian^1,*, Nannan Huang¹, Pauline Puteaux², Xinpeng Zhang¹

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 943-953, 2019, DOI:10.32604/cmc.2019.05768

Abstract Nowadays, emoji image is widely used in social networks. To achieve covert communication in emoji images, this paper proposes a distortion function for emoji images steganography. The profile of image content, the intra- and inter-frame correlation are taken into account in the proposed distortion function to fit the unique properties of emoji image. The three parts are combined together to measure the risks of detection due to the modification on the cover data. With the popular syndrome trellis coding (STC), the distortion of stego emoji image is minimized using the proposed distortion function. As a result, less detectable artifacts could… More >