• Korean Journal of Remote Sensing
• /
• v.34 no.4
• /
• pp.639-647
• /
• 2018

This paper presents TerraSAR-X and KOMPSAT-5 sigma nought variation according to season and antenna observation configuration in Mongolia. Two types of landcover including bare surface and cropland were examined. The seasonal variation of sigma nought in cropland was about 7 dB and particularly a significant sigma nought reduction occurred after harvest. On the contrary, the Mongolia bare surface provides a consistent sigma nought values for several years with an annual variation less than 2.5 dB of standard deviation. However, the bare soil was relatively sensitive to look-direction (or ascending or descending mode) as well as incidence angle while the cropland was almost independent of antenna look-direction and small incidence angle changes. Although the look-directional variation of bare surface sigma nought was observed in this study, the look-direction anisotropic nature of the surface was not well examined. A further study would be required to account for this feature with various SAR observation configurations.

• Journal of Broadcast Engineering
• /
• v.17 no.3
• /
• pp.519-528
• /
• 2012

Voice activity detection (VAD) is generally conducted by extracting features from the acoustic signal and a decision rule. The performance of such VAD algorithms driven by the input acoustic signal highly depends on the acoustic noise. When video signals are available as well, the performance of VAD can be enhanced by using the visual information which is not affected by the acoustic noise. Previous visual VAD algorithms usually use single visual feature to detect the lip activity, such as active appearance models, optical flow or intensity variation. Based on the analysis of the weakness of each feature, we propose to combine intensity change measure and the optical flow in the mouth region, which can compensate for each other's weakness. In order to minimize the computational complexity, we develop simple measures that avoid statistical estimation or modeling. Specifically, the optical flow is the averaged motion vector of some grid regions and the intensity variation is detected by simple thresholding. To extract the mouth region, we propose a simple algorithm which first detects two eyes and uses the profile of intensity to detect the center of mouth. Experiments show that the proposed combination of two simple measures show higher detection rates for the given false positive rate than the methods that use a single feature.

• Architectural research
• /
• v.21 no.4
• /
• pp.91-98
• /
• 2019

In modern times, numerous cities are competing to create the unique skyline adjacent to the water. Tall buildings located across the river have a great contribution to the skyline of a riverfront city and can be a precious asset for the city. Moreover, in several cities, tall buildings and their impact on the urban skyline are a matter that should be considered and regulated in urban design. Therefore, as a prominent element in a larger visual setting of the city, tall buildings should improve the visual quality of the skyline rather than diminish that quality. This research attempts to provide an objective method to analyze the visual quality of the skyline made by a group of tall buildings through their feature of heights and spatial arrangement from riverfront views. The analysis is determined by the design variables of building heights variation, heights transition, density, and spacing of a group of tall buildings. A comparative case study of tall buildings in Yeouido and Lujiazui was conducted to prove the effectiveness of the analysis. The proposed method can be used in a simple way in the quantitative approach to quantify the visual quality of the skyline. In conclusion, Yeuido's skyline is not quite interesting from the riverfront view in terms of height variation and continuity of the skyline view because they are dispersed. Conversely, Lujiazui's skyline from the riverfront vantage points has a good quality in all aspects of the feature of height and spatial arrangements of tall buildings cluster. These factors can be used for the urban designer on how proposed tall buildings within the cluster should appropriately respond to adding image on the skyline.

• Journal of Korea Multimedia Society
• /
• v.9 no.11
• /
• pp.1465-1473
• /
• 2006

In this paper, we present an approach for facial expression recognition using Active Shape Models(ASM) and a state-based model in image sequences. Given an image frame, we use ASM to obtain the shape parameter vector of the model while we locate facial feature points. Then, we can obtain the shape parameter vector set for all the frames of an image sequence. This vector set is converted into a state vector which is one of the three states by the state-based model. In the classification step, we use the k-NN with the proposed similarity measure that is motivated on the observation that the variation-regions of an expression sequence are different from those of other expression sequences. In the experiment with the public database KCFD, we demonstrate that the proposed measure slightly outperforms the binary measure in which the recognition performance of the k-NN with the proposed measure and the existing binary measure show 89.1% and 86.2% respectively when k is 1.

• Journal of Biomedical Engineering Research
• /
• v.28 no.1
• /
• pp.8-16
• /
• 2007

Finite element analysis (FEA) is an effective means for the analysis of bioelectromagnetism. It has been successfully applied to various problems over conventional methods such as boundary element analysis and finite difference analysis. However, its utilization has been limited due to the overwhelming computational load despite of its analytical power. We have previously developed a novel mesh generation scheme that produces FE meshes that are content-adaptive to given MR images. MRI content-adaptive FE meshes (cMeshes) represent the electrically conducting domain more effectively with far less number of nodes and elements, thus lessen the computational load. In general, the cMesh generation is affected by the quality of feature maps derived from MRI. In this study, we have tested various feature maps created based on the improved differential geometry measures for more effective cMesh head models. As performance indices, correlation coefficient (CC), root mean squared error (RMSE), relative error (RE), and the quality of cMesh triangle elements are used. The results show that there is a significant variation according to the characteristics of specific feature maps on cMesh generation, and offer additional choices of feature maps to yield more effective and efficient generation of cMeshes. We believe that cMeshes with specific and improved feature map generation schemes should be useful in the FEA of bioelectromagnetic problems.

• Journal of Internet Computing and Services
• /
• v.8 no.6
• /
• pp.155-167
• /
• 2007

There are four types of human beings according to the Sasang Typology, Oriental medical doctors frequently prescribe healthcare information and treatment depending on one's type, The feature ratios (Table 1) on the human face are the most important criterions to decide which type a patient is. In this paper, we proposed a system to extract these feature ratios from the people's side face, There are two challenges in acquiring the feature ratio: one that selecting representative features; the other, that detecting region of interest from human profile facial image effectively and calculating the feature ratio accurately. In our system, an adaptive color model is used to separate human side face from background, and the method based on geometrical model is designed for region of interest detection. Then we present the error analysis caused by image variation in terms of image size and head pose, To verify the efficiency of the system proposed in this paper, several experiments are conducted using about 173 korean's left side facial photographs. Experiment results shows that the accuracy of our system is increased 17,99% after we combine the front face features with the side face features, instead of using the front face features only.

• Fashion & Textile Research Journal
• /
• v.11 no.5
• /
• pp.788-798
• /
• 2009

This study aims to develop a highly reproducible, optimal frame design algorithm using variations in the curvature of armscye circumference, which will provide the basics for remodeling the 3D human body shape with the concept of reverse design used to develop total contents for the apparel industry. 1. The results of the experiment proved that ratio value was significantly efficient than absolute value of curvature variation to extract feature points in the armscye circumference 2. For the shoulder(1st and 2nd quadrant) and front armhole(3rd quadrant) parts of the armscye circumference, frame remodeling with the positive point of inflection led to the completion of a highly reproducible frame. 3. Similarly, even for the rear armhole part(4th quadrant) in the armscye circumference, it was found that frame remodeling using the positive maximum point of inflection resulted in highly reproducible body shape with the maximum point of inflection situated within the range of split angles $305^{\circ}{\sim}330^{\circ}$, while frame remodeling using simultaneously the two largest points of inflection including maximum point of inflection led to highly reproducible body shape with the maximum point of inflection out of the range $305^{\circ}{\sim}330^{\circ}$. 4. Based upon the optimal frame design algorithm developed in this study, section-specific feature points in the armscye circumference were extracted depending on the rate of curvature variation and remodeling with spline curves was conducted. The results indicate a remarkably high reproducibility(98.6%) and suggest that the algorithm developed in this study is suitable for human body modeling.

• The Plant Pathology Journal
• /
• v.25 no.4
• /
• pp.303-316
• /
• 2009

Genetic variation among the base isolates and monosporidial strains derived from these isolates of Tilletia indica- the causal agent of Karnal bunt (KB) in wheat, was analyzed by morphological, growth behaviors and RAPD-ISSR based molecular polymorphism. Genetic make up of fungal cultures vary among each other. The magnitude of variation in KBPN group is less (narrow genetic base) when compared to the other groups KB3, KB9 and JK (broad genetic base) reflecting that variability is a genetically governed process. The generation of new variation with different growth characteristics is not a generalized feature and is totally dependant on the original genetic make-up of the base isolate generating new monosporidial strains. Thus, it can be concluded that monosporidial strains derived from mono-teliosporic isolate, consists of genetically heterogeneous population. The morphological and genetic variability further suggests that the variation in T. indica strains is predominantly derived through the genetic rearrangements through para sexual means.

• The Research Journal of the Costume Culture
• /
• v.13 no.6 s.59
• /
• pp.896-909
• /
• 2005

In need of studies on the kinds and structure of thread, the biggest variable factor in knitwear patterns, this study attempts: to examine the physical properties by thread type to basically establish systematic data in order to utilize various mixture and structure of yarn and to contribute to the development of optical patterns by building a systemic and scientific methods to produce knit wear patterns though a statistical analysis of the relation between the variations and physical properties. The results is as follows: with time, a feature of knit, which causes instability making it difficult to maintain the original shape, related to material properties, the weight and expansibility recovery rate have the greatest influence on the variation of wale lengths, though the amount varies by material. The variation of course contraction is closely related to density, the dense fabrics showing the highest values, due to the bust of the human body, the wale length variation of the front is greater than that of the back, by a regression analysis of material properties and the variations is obtained showing the weight, density and expansibility recovery rate have the greatest influence on the wale extension and course contraction of knit.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.13 no.5
• /
• pp.894-902
• /
• 2010

This paper presents a vision-based robust off-road terrain classification method against environmental variation. As a supervised classification algorithm, we applied a neural network classifier using wavelet features extracted from wavelet transform of an image. In order to get over an effect of overall image feature variation, we adopted environment sensors and gathered the training parameters database according to environmental conditions. The robust terrain classification algorithm against environmental variation was implemented by choosing an optimal parameter using environmental information. The proposed algorithm was embedded on a processor board under the VxWorks real-time operating system. The processor board is containing four 1GHz 7448 PowerPC CPUs. In order to implement an optimal software architecture on which a distributed parallel processing is possible, we measured and analyzed the data delivery time between the CPUs. And the performance of the present algorithm was verified, comparing classification results using the real off-road images acquired under various environmental conditions in conformity with applied classifiers and features. Experiments show the robustness of the classification results on any environmental condition.