Xianyu Wu¹, Chao Luo¹, Qian Zhang², Jiliu Zhou¹, Hao Yang^{1, 3, *}, Yulian Li¹

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 289-300, 2019, DOI:10.32604/cmc.2019.05990

Abstract Words are the most indispensable information in human life. It is very important to analyze and understand the meaning of words. Compared with the general visual elements, the text conveys rich and high-level moral information, which enables the computer to better understand the semantic content of the text. With the rapid development of computer technology, great achievements have been made in text information detection and recognition. However, when dealing with text characters in natural scene images, there are still some limitations in the detection and recognition of natural scene images. Because natural scene image has more interference and complexity than… More >

Qi He¹, Shui Yu², Huifang Xu^3,*, Jia Liu⁴, Dongmei Huang⁵, Guohua Liu⁶, Fangqin Xu³, Yanling Du¹

CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 349-361, 2019, DOI:10.32604/cmc.2019.03703

Abstract The recent advances in remote sensing and computer techniques give birth to the explosive growth of remote sensing images. The emergence of cloud storage has brought new opportunities for storage and management of massive remote sensing images with its large storage space, cost savings. However, the openness of cloud brings challenges for image data security. In this paper, we propose a weighted image sharing scheme to ensure the security of remote sensing in cloud environment, which takes the weights of participants (i.e., cloud service providers) into consideration. An extended Mignotte sequence is constructed according to the weights of participants, and… More >

Xintao Duan^1,*, Haoxian Song¹, Chuan Qin², Muhammad Khurram Khan³

CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 483-493, 2018, DOI: 10.3970/cmc.2018.01798

Abstract In this paper, we propose a novel coverless image steganographic scheme based on a generative model. In our scheme, the secret image is first fed to the generative model database, to generate a meaning-normal and independent image different from the secret image. The generated image is then transmitted to the receiver and fed to the generative model database to generate another image visually the same as the secret image. Thus, we only need to transmit the meaning-normal image which is not related to the secret image, and we can achieve the same effect as the transmission of the secret image.… More >

Yang Du¹, Zhaoxia Yin^1,2,*, Xinpeng Zhang³

CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 495-507, 2018, DOI: 10.3970/cmc.2018.02440

Abstract This paper proposes a lossless and high payload data hiding scheme for JPEG images by histogram modification. The most in JPEG bitstream consists of a sequence of VLCs (variable length codes) and the appended bits. Each VLC has a corresponding RLV (run/length value) to record the AC/DC coefficients. To achieve lossless data hiding with high payload, we shift the histogram of VLCs and modify the DHT segment to embed data. Since we sort the histogram of VLCs in descending order, the filesize expansion is limited. The paper’s key contribution includes: Lossless data hiding, less filesize expansion in identical pay-load and… More >

Yangyang Wang¹, Rongrong Ni^1,*, Yao Zhao¹, Min Xian²

CMC-Computers, Materials & Continua, Vol.55, No.2, pp. 255-265, 2018, DOI:10.3970/cmc.2018.01732

Abstract In this paper, two methods are proposed to embed visual watermark into direct binary search (DBS) halftone images, which are called Adjusted Direct Binary Search (ADBS) and Dual Adjusted Direct Binary Search (DADBS). DADBS is an improved version of ADBS. By using the proposed methods, the visual watermark will be embedded into two halftone images separately, thus, the watermark can be revealed when these two halftone images are overlaid. Experimental results show that both methods can achieve excellent image visual quality and decoded visual patterns. More >

Qi Cui^1,2,*, Suzanne McIntosh³, Huiyu Sun³

CMC-Computers, Materials & Continua, Vol.55, No.2, pp. 229-241, 2018, DOI:10.3970/cmc.2018.01693

Abstract Currently, some photorealistic computer graphics are very similar to photographic images. Photorealistic computer generated graphics can be forged as photographic images, causing serious security problems. The aim of this work is to use a deep neural network to detect photographic images (PI) versus computer generated graphics (CG). In existing approaches, image feature classification is computationally intensive and fails to achieve real-time analysis. This paper presents an effective approach to automatically identify PI and CG based on deep convolutional neural networks (DCNNs). Compared with some existing methods, the proposed method achieves real-time forensic tasks by deepening the network structure. Experimental results… More >

Yi Cao^1,2, Zhili Zhou^1,2,3, Xingming Sun^1,2, Chongzhi Gao^4,*

CMC-Computers, Materials & Continua, Vol.54, No.2, pp. 197-207, 2018, DOI:10.3970/cmc.2018.054.197

Abstract The traditional information hiding methods embed the secret information by modifying the carrier, which will inevitably leave traces of modification on the carrier. In this way, it is hard to resist the detection of steganalysis algorithm. To address this problem, the concept of coverless information hiding was proposed. Coverless information hiding can effectively resist steganalysis algorithm, since it uses unmodified natural stego-carriers to represent and convey confidential information. However, the state-of-the-arts method has a low hidden capacity, which makes it less appealing. Because the pixel values of different regions of the molecular structure images of material (MSIM) are usually different,… More >