• 한국HCI학회:학술대회논문집
• /
• 2006.02a
• /
• pp.355-361
• /
• 2006

In large scale environments like airport, museum, large warehouse and department store, autonomous mobile robots will play an important role in security and surveillance tasks. Robotic security guards will give the surveyed information of large scale environments and communicate with human operator with that kind of data such as if there is an object or not and a window is open. Both for visualization of information and as human machine interface for remote control, a 3D model can give much more useful information than the typical 2D maps used in many robotic applications today. It is easier to understandable and makes user feel like being in a location of robot so that user could interact with robot more naturally in a remote circumstance and see structures such as windows and doors that cannot be seen in a 2D model. In this paper we present our simple and easy to use method to obtain a 3D textured model. For expression of reality, we need to integrate the 3D models and real scenes. Most of other cases of 3D modeling method consist of two data acquisition devices. One for getting a 3D model and another for obtaining realistic textures. In this case, the former device would be 2D laser range-finder and the latter device would be common camera. Our algorithm consists of building a measurement-based 2D metric map which is acquired by laser range-finder, texture acquisition/stitching and texture-mapping to corresponding 3D model. The algorithm is implemented with laser sensor for obtaining 2D/3D metric map and two cameras for gathering texture. Our geometric 3D model consists of planes that model the floor and walls. The geometry of the planes is extracted from the 2D metric map data. Textures for the floor and walls are generated from the images captured by two 1394 cameras which have wide Field of View angle. Image stitching and image cutting process is used to generate textured images for corresponding with a 3D model. The algorithm is applied to 2 cases which are corridor and space that has the four wall like room of building. The generated 3D map model of indoor environment is shown with VRML format and can be viewed in a web browser with a VRML plug-in. The proposed algorithm can be applied to 3D model-based remote surveillance system through WWW.

• Journal of Broadcast Engineering
• /
• v.20 no.2
• /
• pp.204-214
• /
• 2015

Depth map upsampling is an approach to increase the spatial resolution of depth maps obtained from a depth camera. Depth map quality is closely related to 3D perception of stereoscopic image, multi-view image and holography. In general, the performance of upsampled depth map is evaluated by PSNR (Peak Signal to Noise Ratio). On the other hand, time-consuming 3D subjective tests requiring human subjects are carried out for examining the 3D perception as well as visual fatigue for 3D contents. Therefore, if an objective metric is closely correlated with a subjective test, the latter can be replaced by the objective metric. For this, this paper proposes a best metric by investigating the relationship between diverse objective metrics and 3D subjective tests. Diverse reference and no-reference metrics are adopted to evaluate the performance of upsampled depth maps. The subjective test is performed based on DSCQS test. From the utilization and analysis of three kinds of correlations, we validated that SSIM and Edge-PSNR can replace the subjective test.

• Journal of Acupuncture Research
• /
• v.21 no.2
• /
• pp.223-233
• /
• 2004

Objective: As a manual accupucture method, the twirling-needle treatment has been known more effective in relieving pain than the conventional simple accupuncture treatment. Finding a proper treatment condition is difficult because of the lack of a quantative measurement of the alleviation of pain made by acupuncture. In this research, the authors propose the use of infrared thermal images in a formalin test to quantatively verify the effect of twirling. Methods: After injecting 10%~20% formalin into the tail of rats, the infrared thermal images(ITI) have been obtained to estimate the thermal distribution caused by inflammation. The authors propose a processing method to measure the thermal distribution from the thermal images obtained from the infrared camera as a pain model of the formalin test. Results: The pain model obtained from the infrared thermal image has two phases. The first phase, which is a transient period, is the initial 20 minutes when the pain is developed after the formalin injection. The second phase, which is a steady state, is where the development of pain lasts for 60 minutes or more after the first stage. This characteristic of the proposed model based on ITI is consistent with that of the pain model reported by other researchers whose works are based on the time-course of flinching and licking/biting, following a different concentration of formalin. It is noticed that the response of the thermal distribution obtained from ITI shows very high correlation to the behavioral response in the formalin test performed by Kazuhiro Okuda and four others5). In addition, the authors propose an ITI method to determine the pain-reducing effect of the acupuncture. The thermal distribution obtained from the experiment shows that there is significant pain reducing effect made by the twirling-needle method.

• Journal of Korea Game Society
• /
• v.10 no.2
• /
• pp.49-56
• /
• 2010

In this paper, we propose a control method of virtual hand by the recognition of a user's hand in the virtual reality game environment. We display virtual hand on the game screen after getting the information of the user's hand movement and the direction thru input images by camera. We can utilize the movement of a user's hand as an input interface for virtual hand to select and move the object. As a hand recognition method based on the vision technology, the proposed method transforms input image from RGB color space to HSV color space, then segments the hand area using double threshold of H, S value and connected component analysis. Next, The center of gravity of the hand area can be calculated by 0 and 1 moment implementation of the segmented area. Since the center of gravity is positioned onto the center of the hand, the further apart pixels from the center of the gravity among the pixels in the segmented image can be recognized as fingertips. Finally, the axis of the hand is obtained as the vector of the center of gravity and the fingertips. In order to increase recognition stability and performance the method using a history buffer and a bounding box is also shown. The experiments on various input images show that our hand recognition method provides high level of accuracy and relatively fast stable results.

• The Journal of Korean Academy of Prosthodontics
• /
• v.40 no.5
• /
• pp.484-492
• /
• 2002

The selection of the maxillary anterior artificial teeth is made primarily for esthetics and they must be in harmony with the surrounding oral environment. However the selection of artificial teeth is based on the large degree of subjective judgement or the dentists, therefore, this is one of the most unscientific processes. This study was performed to determine clinically whether there is correlation among the width of the maxillary central incisor(WMCI), the intercanine distance (ICD) the facial width(FW), and the interalar nasal width(IAW) in Korean adults, and to provide the selection standards for the maxillary anterior artificial teeth. The casts were obtained from 91 undergraduate dental students(49 males and 42 females) with Angle's class I occlusion presenting well-arranged intact anterior teeth. The WMCI and ICD were measured on the casts with a vernier calipers($Miltex^{(R)}$, Germany). The photographic procedures under standardized conditions were performed to record each subject's frontal face using digital camera($Olympus^{(R)}$, C-2500L, Japan). The FW and IAW were measured with image analyzer($Image-Pro^{(R)}$ PLUS. media cybermetrics. USA). The results were obtained as follows : 1. The mean WMCI was $8.11{\pm}0.67mm$, ICD was $37.88{\pm}2.15mm$, FW was $141.29{\pm}5.84mm$. and IAW was $37.85{\pm}2.29 mm$. 2. The ratios of FW/WMCI, FW/ICD, IAW/ICD were 17.4, 3.7, 1.0 respectively. 3. All measurements(WMCI, ICD, FW, and IAW) of male group were longer than those of female group significantly in Student's t-test(p<0.01). 4. There was significant correlation between WMCI, ICD, FW, and IAW in Pearson's correlation analysis(p<0.01). 5, The relationship between IAW and ICD shows the strongest correlation among six combinations in linear regression analysis($R^2$=0.753, Y=7.046+0.815X). The FW and IAW could be very reliable guides for the selection of the maxillary anterior artificial teeth.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.40 no.4
• /
• pp.437-444
• /
• 2020

A lunar rover's optical camera is used to provide navigation and terrain information in an exploration zone. However, due to the scant presence of atmosphere, the Moon has homogeneous terrain with dark soil. Also, in extreme environments, the rover has limited data storage with low computation capability. Thus, for successful exploration, it is required to examine feature detection and matching methods which are robust to lunar terrain and environmental characteristics. In this research, SIFT, SURF, BRISK, ORB, and AKAZE are comparatively analyzed with lunar terrain images from a lunar rover. Experimental results show that SIFT and AKAZE are most robust for lunar terrain characteristics. AKAZE detects less quantity of feature points than SIFT, but feature points are detected and matched with high precision and the least computational cost. AKAZE is adequate for fast and accurate navigation information. Although SIFT has the highest computational cost, the largest quantity of feature points are stably detected and matched. The rover periodically sends terrain images to Earth. Thus, SIFT is suitable for global 3D terrain map construction in that a large amount of terrain images can be processed on Earth. Study results are expected to provide a guideline to utilize feature detection and matching methods for future lunar exploration rovers.

• Journal of Broadcast Engineering
• /
• v.21 no.3
• /
• pp.425-435
• /
• 2016

In this paper, we propose a classification model by analyzing raw material images recorded using a color CCD camera to automatically classify good and defective agricultural products such as rice, coffee, and green tea, and raw materials. The current classifying agricultural products mainly depends on visual selection by skilled laborers. However, classification ability may drop owing to repeated labor for a long period of time. To resolve the problems of existing human dependant commercial products, we propose a vision based automatic raw material classification combining mean shift clustering and stepwise region merging algorithm. In this paper, the image is divided into N cluster regions by applying the mean-shift clustering algorithm to the foreground map image. Second, the representative regions among the N cluster regions are selected and stepwise region-merging method is applied to integrate similar cluster regions by comparing both color and positional proximity to neighboring regions. The merged raw material objects thereby are expressed in a 2D color distribution of RG, GB, and BR. Third, a threshold is used to detect good and defective products based on color distribution ellipse for merged material objects. From the results of carrying out an experiment with diverse raw material images using the proposed method, less artificial manipulation by the user is required compared to existing clustering and commercial methods, and classification accuracy on raw materials is improved.

• Journal of Broadcast Engineering
• /
• v.25 no.2
• /
• pp.200-207
• /
• 2020

Recently, deep neural networks such as CNN are showing excellent performance in various fields such as image classification, object recognition, visual quality enhancement, etc. However, as the model size and computational complexity of deep learning models for most applications increases, it is hard to apply neural networks to IoT and mobile environments. Therefore, neural network compression algorithms for reducing the model size while keeping the performance have been being studied. In this paper, we apply few compression methods to CNN models and evaluate their performances in the embedded environment. For evaluate the performance, the classification performance and inference time of the original CNN models and the compressed CNN models on the image inputted by the camera are evaluated in the embedded board equipped with QCS605, which is a customized AI chip. In this paper, a few CNN models of MobileNetV2, ResNet50, and VGG-16 are compressed by applying the methods of pruning and matrix decomposition. The experimental results show that the compressed models give not only the model size reduction of 1.3~11.2 times at a classification performance loss of less than 2% compared to the original model, but also the inference time reduction of 1.2~2.21 times, and the memory reduction of 1.2~3.8 times in the embedded board.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.18 no.2
• /
• pp.28-32
• /
• 2014

Purpose Patient motion during myocardial perfusion SPECT can produce images that show visual artifacts and perfusion defects. This artifacts and defects remain a significant source of unsatisfactory myocardial perfusion SPECT. Motion correction has been developed as a way to correct and detect the patient motion for reducing artifacts and defects, and each motion correction uses different algorithm. We corrected simulated motion patterns with several motion correction methods and compared those images. Materials and Methods Phantom study was performed. The anthropomorphic torso phantom was made with equal counts from patient's body and simulated defect was added in myocardium phantom for to observe the change in defect. Vertical motion was intentionally generated by moving phantom downward in a returning pattern and in a non-returning pattern throughout the acquisition. In addition, Lateral motion was generated by moving phantom upward in a returning pattern and in a non-returning pattern. The simulated motion patterns were detected and corrected similarly to no-motion pattern image and QPS score, after Motion Detection and Correction Method (MDC), stasis, Hopkins method were applied. Results In phantom study, Changes of perfusion defect were shown in the anterior wall by the simulated phantom motions, and inferior wall's defect was found in some situations. The changes derived from motion were corrected by motion correction methods, but Hopkins and Stasis method showed visual artifact, and this visual artifact did not affect to perfusion score. Conclusion It was confirmed that motion correction method is possible to reduce the motion artifact and artifactual perfusion defect, through the apply on the phantom tests. Motion Detection and Correction Method (MDC) performed better than other method with polar map image and perfusion score result.

• Journal of the Korean Graphic Arts Communication Society
• /
• v.21 no.2
• /
• pp.43-53
• /
• 2003

As information-communication network has been developed rapidly, internet users' circumstances also have been changed for the better, in result, more information can be applied than before. At this moment, there are many differences between real color and reappeared color on the CRT. When we observe a material object, our eyes perceive the multiplied form of light sources and nature spectral reflection. However, when the photographed signal is reappeared, illumination at that time of photographing and spectral reflection of a material object are converted into signal, and this converted RGB signal is observed on the CRT under another illumination. At this time, RGB signal is the reflected result of illumination at that time of photographing Therefore, this signal is influenced by the illumination at present, so it can be perceived another color. To accord the colro reflections of another color source, the study has been reported by S.C.Ahn$^{[1]}$, which study is about the color reapperarance system using neuron network. Furthermore, color reappearing method become independent of its circumstances has been reported by Y.Miyake$^{[2]}$. This method can make the same illuminations even if the observe circumstances are changed. To assume the light sources of observe circumstances, the study about color reappearing system using CCD sensor also have been studied by S.C.Ahn$^{[3]}$. In these studies, a population is fixed, first, on ab coordinates of CIE L${\ast}$a${\ast}$b${\ast}$. Then, color reappearing can be possible using every population and existing digital camera. However, the color is changed curvedly, not straightly, according to value's changes on the ab coordinates of CIE L${\ast}$a${\ast}$b. To solve these problems in this study, first of all, Labeling techniques are introduced. Next, basis color-it is based on Munsell color system-is divided into 10 color fields. And then, 4 special color- skin color, grass color, sky color, and gray-are added to the basis color. Finally, 14 color fields are fixed. After analyzing of the principle elements of new-defined-color fields' population, utility value and propriety value are going to be examined in 3-Band system from now on.