• Journal of the Optical Society of Korea
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• v.17 no.5
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• pp.399-404
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• 2013

This article proposes a digital image correlation (DIC) strain measurement method based on a finite element (FE) algorithm. A two-step digital image correlation is presented. In the first step, the gradient-based subpixels technique is used to search the displacements of a region of interest of the specimen, and then the strain fields are obtained by utilizing the finite element method in the second step. Both simulation and experiment processing, including tensile strain deformation, show that the proposed method can achieve nearly the same accuracy as the cubic spline interpolation method in most cases and higher accuracy in some cases, such as the simulations of uniaxial tension with and without noise. The results show that it also has a good noise-robustness. Finally, this method is used in the uniaxial tensile testing for Dahurian Larch wood specimens with or without a hole, and the obtained strain values are close to the results which were obtained from the strain gauge and the cubic spline interpolation method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.524-543
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• 2022

Correct facade image parsing is essential to the semantic understanding of outdoor scenes. Unfortunately, there are often various occlusions in front of buildings, which fails many existing methods. In this paper, we propose an end-to-end deep network for facade parsing with occlusions. The network learns to decompose an input image into visible and invisible parts by occlusion reasoning. Then, a context aggregation module is proposed to collect nonlocal cues for semantic segmentation of the visible part. In addition, considering the regularity of man-made buildings, a repetitive pattern completion branch is designed to infer the contents in the invisible regions by referring to the visible part. Finally, the parsing map of the input facade image is generated by fusing the results of the visible and invisible results. Experiments on both synthetic and real datasets demonstrate that the proposed method outperforms state-of-the-art methods in parsing facades with occlusions. Moreover, we applied our method in applications of image inpainting and 3D semantic modeling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1043-1064
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• 2020

A kind of Subjective Imaging Effect Assessment (SIEA) method and its applications on intelligent imaging terminal design in engineering site are presented. First, some visual assessment indices are used to characterize the imaging effect: the image brightness, the image brightness uniformity, the color image contrast, the image edge blur, the image color difference, the image saturation, the image noise, and the integrated imaging effect index. A linear weighted function is employed to carry out the SIEA computation and the Analytic Hierarchy Process (AHP) technique is used to estimate its weights. Second, a SIEA software is developed. It can play images after the settings of assessment index or assessment reaction time, etc. Third, two cases are used to illustrate the application effects of proposed method: the image enhancement system design for surveillance camera and the imaging environment perception system design for intelligent lighting terminal. A Prior Sequential Stimulus (PSS) experiment is proposed to improve the evaluation stability of SIEA method. Many experiment results have shown the proposed method can realize a stable system design or parameters setting for the intelligent imaging terminal in engineering site.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3942-3961
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• 2019

Recently, the models of deep super-resolution networks can successfully learn the non-linear mapping from the low-resolution inputs to high-resolution outputs. However, for large scaling factors, this approach has difficulties in learning the relation of low-resolution to high-resolution images, which lead to the poor restoration. In this paper, we propose Stage Generative Adversarial Networks (Stage-GAN) with semantic maps for image super-resolution (SR) in large scaling factors. We decompose the task of image super-resolution into a novel semantic map based reconstruction and refinement process. In the initial stage, the semantic maps based on the given low-resolution images can be generated by Stage-0 GAN. In the next stage, the generated semantic maps from Stage-0 and corresponding low-resolution images can be used to yield high-resolution images by Stage-1 GAN. In order to remove the reconstruction artifacts and blurs for high-resolution images, Stage-2 GAN based post-processing module is proposed in the last stage, which can reconstruct high-resolution images with photo-realistic details. Extensive experiments and comparisons with other SR methods demonstrate that our proposed method can restore photo-realistic images with visual improvements. For scale factor ${\times}8$, our method performs favorably against other methods in terms of gradients similarity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2400-2419
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• 2014

Pre-segmented pixels can reduce the difficulty of segmentation and promote the segmentation performance. This paper proposes a novel segmentation method based on merging texture superpixels by computing inner similarity. Firstly, we design a set of Gabor filters to compute the amplitude responses of original image and compute the texture map by a salience model. Secondly, we employ the simple clustering to extract superpixles by affinity of color, coordinates and texture map. Then, we design a normalized histograms descriptor for superpixels integrated color and texture information of inner pixels. To obtain the final segmentation result, all adjacent superpixels are merged by the homogeneity comparison of normalized color-texture features until the stop criteria is satisfied. The experiments are conducted on natural scene images and synthesis texture images demonstrate that the proposed segmentation algorithm can achieve ideal segmentation on complex texture regions.

• BMB Reports
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• v.52 no.4
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• pp.277-282
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• 2019

Currently speaking, it is noted that radiofrequency ablation (RFA) has been the most widely used treatment for hepatocellular carcinoma (HCC) occurring in patients. However, accumulating evidence has demonstrated that the incidence of insufficient RFA (IRFA) may result in the identified rapid progression of residual HCC in the patient, which can greatly hinder the effectiveness and patient reported benefits of utilizing this technique. Although many efforts have been proposed, the underlying mechanisms triggering the rapid progression of residual HCC after IRFA have not yet been fully clarified through current research literature reviews. It was shown in this study that cell proliferation, migration and invasion of residual HepG2 and SMMC7721 cells were significantly increased after the IRFA was simulated in vitro. In other words, it is noted that IRFA could do this by enhancing the image of autophagy of the residual HCC cell via the $HIF-1{\alpha}/BNIP3$ pathway. Consequently, the down-regulation of BNIP3 may result in the inhibition of the residual HCC cell progression and autophagy after IRFA. Our present study results suggest that IRFA could promote residual HCC cell progression in vitro by enhancing autophagy via the $HIF-1{\alpha}/BNIP3$ pathway. For this reason, it is noted that the targeting of the BNIP3 may be useful in preventing the rapid growth and metastasis of residual HCC after IRFA.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.593-599
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• 2013

China's Mapping Satellite-1, developed by the China Aerospace Science and Technology Corporation (CASC), was launched in three years ago. The data from Mapping Satellite-1 are able to use for efficient surveying and geometric mapping application field. In this paper, we fuse the panchromatic and multispectral images of Changchun area, which are obtained from the Mapping Satellite-1, the one that is the Chinese first transmission-type three-dimensional mapping satellite. The four traditional image fusion methods, which are HPF, Mod.IHS, Panshar and wavelet transform, were used to approach for effectively fusing Mapping Satellite-1 remote sensing data. Subsequently we assess the results with some commonly used methods, which are known a subjective qualitative evaluation and quantitative statistical analysis approach. Consequently, we found that the wavelet transform remote sensing image fusion is the optimal in the degree of distortion, the ability of performance of details and image information availability among four methods. To further understand the optimal methods to fuse Mapping Satellite-1 images, an additional study is necessary.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1843-1859
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• 2013

The continuous increase of the spatial resolution of remote sensing images brings great challenge to image analysis and processing. Traditional prior knowledge-based region detection and target recognition algorithms for processing high resolution remote sensing images generally employ a global searching solution, which results in prohibitive computational complexity. In this paper, a more efficient region of interest (ROI) detection algorithm based on visual attention and threshold segmentation (VA-TS) is proposed, wherein a visual attention mechanism is used to eliminate image segmentation and feature detection to the entire image. The input image is subsampled to decrease the amount of data and the discrete moment transform (DMT) feature is extracted to provide a finer description of the edges. The feature maps are combined with weights according to the amount of the "strong points" and the "salient points". A threshold segmentation strategy is employed to obtain more accurate region of interest shape information with the very low computational complexity. Experimental statistics have shown that the proposed algorithm is computational efficient and provide more visually accurate detection results. The calculation time is only about 0.7% of the traditional Itti's model.

• Journal of the Korean Society of Costume
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• v.56 no.2 s.101
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• pp.32-44
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• 2006

Denim has been one of the most favored clothing item among young people regardless of regional difference. This study compared the styling of women's denim fashion in two Asian metro-cities, Seoul and Beijing, in order to understand how differ the fashion taste of both cities. Data was collected by taking photos of young women who wear denim clothing at the main streets of downtowns or famous shopping areas of both cities from the July of 2004 till the April of 2005. A total of 524 photos(Seoul 242, and Beijing 282) were put into content analysis. Results showed that there were several similarities and differences in denim styling between two cities in terms of the most widely worn denim items and the coordinate items, and the favored colors, silhouette, details of denim pants and the coordinate items. In Seoul, women favored denim look with little detail, fitted silhouette, and in more formal image. A few denim styles prevailed in each season which reflect current denim fashion trends. Meanwhile a wide variety of denim styles were found at Beijing without dominant denim trends, which means Beijing women put more emphasis on personal expression of their fashion taste instead of just following fashion trends.

• Current Optics and Photonics
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• v.6 no.2
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• pp.151-160
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• 2022

Fundus images can reflect ocular diseases and systemic diseases such as glaucoma, diabetes mellitus, and hypertension. Thus, research on fundus-detection equipment is of great importance. The fundus camera has been widely used as a kind of noninvasive detection equipment. Most existing devices can only obtain two-dimensional (2D) retinal-image information, yet the fundus of the human eye also has spectral characteristics. The fundus has many pigments, and their different distributions in the eye lead to dissimilar tissue penetration for light waves, which can reflect the corresponding fundus structure. To obtain more abundant information and improve the detection level of equipment, a snapshot nonmydriatic fundus imaging spectral system, including fundus-imaging spectrometer and illumination system, is studied in this paper. The system uses a microlens array to realize snapshot technology; information can be obtained from only a single exposure. The system does not need to dilate the pupil. Hence, the operation is simple, which reduces its influence on the detected object. The system works in the visible and near-infrared bands (550-800 nm), with a volume less than 400 mm × 120 mm × 75 mm and a spectral resolution better than 6 nm.