Li-Hong Juang^a, Ming-Ni Wu^b, Feng-Mao Tsou^b

Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 739-745, 2018, DOI:10.1080/10798587.2017.1327549

Abstract Kinect(+openCV); Dynamic portrait segmentation; Skeletal tracking; Edge transparent processing; Video interactive More >

Hanying Tang^1,2, Meng Ye^1,2, Zhiqing E. Zhou³, Zhiyi Gan^1,2,*, Hongyu Ma^1,2,*

International Journal of Mental Health Promotion, Vol.20, No.1, pp. 27-40, 2018, DOI:10.32604/IJMHP.2018.010734

Abstract Work-related use of ICT (W_ICT) at home has been found to relate to important employee outcomes in their work and family lives. However, little is known about how individuals can actively apply strategies or tactics to utilize the advantages or reduce the disadvantages of W_ICT. In the current study, based on boundary theory, we examined the interaction effect of segmentation preference and boundary control in creating the boundary around W_ICT and its subsequent positive effect on individuals’ psychological detachment. Results based on a sample of 560 Chinese full-time employees showed that only for individuals with More >

Yuxiang Huang¹, Chuliu He¹, Jiaqiu Wang², Yuehong Miao¹, Tongjin Zhu¹, Ping Zhou¹, Zhiyong Li^1,2,*

Molecular & Cellular Biomechanics, Vol.15, No.2, pp. 117-125, 2018, DOI:10.3970/mcb.2018.02478

Abstract Intravascular optical coherence tomography (IVOCT) is becoming more and more popular in clinical diagnosis of coronary atherosclerotic. However, reading IVOCT images is of large amount of work. This article describes a method based on image feature extraction and support vector machine (SVM) to achieve semi-automatic segmentation of IVOCT images. The image features utilized in this work including light attenuation coefficients and image textures based on gray level co-occurrence matrix. Different sets of hyper-parameters and image features were tested. This method achieved an accuracy of 83% on the test images. Single class accuracy of 89% for More >

Qili Zhou¹, Yongbin Qiu¹, Li Li^1,*, Jianfeng Lu¹, Wenqiang Yuan¹, Xiaoqing Feng², Xiaoyang Mao³

CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 151-163, 2018, DOI:10.3970/cmc.2018.055.151

Abstract Steganography technology has been widely used in data transmission with secret information. However, the existing steganography has the disadvantages of low hidden information capacity, poor visual effect of cover images, and is hard to guarantee security. To solve these problems, steganography using reversible texture synthesis based on seeded region growing and LSB is proposed. Secret information is embedded in the process of synthesizing texture image from the existing natural texture. Firstly, we refine the visual effect. Abnormality of synthetic texture cannot be fully prevented if no approach of controlling visual effect is applied in the More >

K. Naveen Kumar¹, K. Srinivasa Rao², Y. Srinivas³, Ch. Satyanarayana⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.107, No.3, pp. 201-221, 2015, DOI:10.3970/cmes.2015.107.201

Abstract Texture Analysis is one of the prime considerations for image analysis and processing. Texture segmentation gained lot of importance due to its ready applicability in automation of scene identification and computer vision. Several texture segmentation methods have been developed and analysed with the assumption that the feature vector associated with the texture of the image region is modelled as Gaussian mixture model. Due to the limitations of the Gaussian model being meso kurtic, it may not characterise the texture of all image regions accurately. Hence in this paper, a texture segmentation algorithm is developed and… More >

Jia Dongyao^1,2, Zhu Huaihua¹, Ai Yanke¹, Zou Shengxiong¹

CMES-Computer Modeling in Engineering & Sciences, Vol.103, No.6, pp. 411-427, 2014, DOI:10.3970/cmes.2014.103.411

Abstract The existing study on the image segmentation methods based on the image of vehicle lights is insufficient both at home and abroad, and its segmentation efficiency and accuracy is low as well. On the basis of the analysis of the regional characteristics of vehicle lights and a level set model, an image segmentation method for complex vehicle lights based on adaptive significance level set contour model is proposed in this paper. Adaptive positioning algorithm of the significant initial contour curve based on two-dimensional convex hull is designed to obtain the initial position of evolution curve,… More >

R. V. Uddanwadiker^*

Molecular & Cellular Biomechanics, Vol.10, No.4, pp. 289-302, 2013, DOI:10.3970/mcb.2013.010.289

Abstract The aim of the study is to find most optimum combination of crown material and adhesive to avoid loosening and thereby failure of restored tooth. This study describes the Thermo-Mechanical analysis of restored molar tooth crown for determination of the stress levels due to thermal and mechanical loads on restored molar tooth. The potential use of the 3-D model was demonstrated and analyzed using different materials for crown. Thermal strain, stress and deformation were measured at hot and cold conditions in ANSYS and correlated with analytical calculation and existing experimental data for model validation and More >

Foued Derraz¹, Laurent Peyrodie², Antonio PINTI³, Abdelmalik Taleb-Ahmed³, Azzeddine Chikh⁴, Patrick Hautecoeur⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.67, No.2, pp. 95-118, 2010, DOI:10.3970/cmes.2010.067.095

Abstract We propose a new semi-automatic segmentation based Active Contour Model and statistic prior knowledge of Multiple Sclerosis (MS) Lesions in Regions Of Interest (RIO) within brain Magnetic Resonance Images(MRI). Reliable segmentation of MS lesion is important for at least three types of practical applications: pharmaceutical trails, making decision for drug treatment, patient follow-up. Manual segmentation of the MS lesions in brain MRI by well qualified experts is usually preferred. However, manual segmentation is hard to reproduce and can be highly cost and time consuming in the presence of large volume of MRI data. In other… More >

Maria João M. Vasconcelos¹, João Manuel R. S. Tavares¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.10, No.1, pp. 3-4, 2009, DOI:10.3970/icces.2009.010.003

Abstract In the last years, researchers from the Computational Vision working field have been developing new methods to perform image segmentation for human motion analysis. The development of computational techniques suitable to automatically identify the structures involved is necessary to obtain more representative and robust features to be further used in the analysis of human motion from image sequences.
The first step of human motion analysis from image sequences is strongly related with image segmentation. In fact, the first goal of any system designed for this aim is the identification of the structures’ features to be analysed… More >

Patrícia C.T. Gonçalves^1,2, João Manuel R.S. Tavares¹, R.M. Natal Jorge¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.9, No.3, pp. 203-204, 2009, DOI:10.3970/icces.2009.009.203

Abstract The main goals of the present work are to automatically extract the contour of an object and to simulate its deformation using a physical approach. In this work, to segment an object represented in an image, an initial contour is manually defined for it that will then automatically evolve until it reaches the border of the desired object. In this approach, the contour is modelled by a physical formulation using the finite element method, and its temporal evolution to the desired final contour is driven by internal and external forces. The internal forces are defined… More >