• Restorative Dentistry and Endodontics
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• v.33 no.2
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• pp.141-147
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• 2008

This study was aimed to develop an instrument for real-time measurement of fluid conductance and to investigate the hydrodynamics of dentinal fluid. The instrument consisted of three parts; (1) a glass capillary and a photo sensor for detection of fluid movement, (2) a servo-motor, a lead screw and a ball nut for tracking of fluid movement, (3) a rotary encoder and software for data processing. To observe the blocking effect of dentinal fluid movement, oxalate gel and self-etch adhesive agent were used. BisBlock (Bisco) and Clearfil SE Bond (Kuraray) were applied to the occlusal dentin surface of extracted human teeth. Using this new device, the fluid movement was measured and compared between before and after each agent was applied. The instrument was able to measure dentinal fluid movement with a high resolution (0.196 nL) and the flow occurred with a rate of 0.84 to 15.2 nL/s before treatment. After BisBlock or Clearfil SE Bond was used, the fluid movement was decreased by 39.8 to 89.6%.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.3
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• pp.177-186
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• 2012

In this paper, we propose a real-time approach for detecting and tracking a hand region by analyzing depth images. We build a hand model in advance. The model has the shape information of a hand. The detecting process extracts out moving areas in an image, which are possibly caused by moving a hand in front of a camera. The moving areas can be identified by analyzing accumulated difference images and applying the region growing technique. The extracted moving areas are compared against a hand model to get justified as a hand region. The tracking process keeps the track of center points of hand regions of successive frames. For this purpose, it involves three steps. The first step is to determine a seed point that is the closest point to the center point of a previous frame. The second step is to perform region growing to form a candidate region of a hand. The third step is to determine the center point of a hand to be tracked. This point is searched by the mean-shift algorithm within a confined area whose size varies adaptively according to the depth information. To verify the effectiveness of our approach, we have evaluated the performance of our approach while changing the shape and position of a hand as well as the velocity of hand movement.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.3
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• pp.187-194
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• 2012

Prostate cancer is one of the most frequent cancers in men and is a major cause of mortality in the most of countries. In many diagnostic and treatment procedures for prostate disease, transrectal ultrasound(TRUS) images are being used because the cost is low. But, accurate detection of prostate boundaries is a challenging and difficult task due to weak prostate boundaries, speckle noises and the short range of gray levels. This paper proposes a method for automatic prostate segmentation in TRUS images using its average shape model and invariant features. This approach consists of 4 steps. First, it detects the probe position and the two straight lines connected to the probe using edge distribution. Next, it acquires 3 prostate patches which are in the middle of average model. The patches will be used to compare the features of prostate and nonprostate. Next, it compares and classifies which blocks are similar to 3 representative patches. Last, the boundaries from prior classification and the rough boundaries from first step are used to determine the segmentation. A number of experiments are conducted to validate this method and results showed that this new approach extracted the prostate boundary with less than 7.78% relative to boundary provided manually by experts.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.4
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• pp.195-202
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• 2016

There have been many studies on subject tests for 3D contents using 3D glasses, but there is a limited research for 3D contents using autostereoscopic display. In this study, we investigated to assess usability of electroencephalogram (EEG) as an objective evaluation for 3D contents with different quality using autosteroscopic display, especially for lenticular lens type. The image with optimal quality and the image with distorted quality were separately generated for autostereosopic display with lenticular lens type and displayed sequentially through lenticular lens for 26 subjects. EEG signals of 8 channels from 26 subjects exposed to those images were detected and correlation between EEG signal and the quality of 3D images were statistically evaluated to check differences between optimal and distorted 3D contents. What we found was that there was no statistical significance for a wave vibration, however b wave vibration shows statistically significant between optimal and distorted 3D contents. b wave vibration observed for the distorted 3D image was stronger than that for the optimal 3D image. This results suggest that subjects viewing the distorted 3D contents through lenticular lens experience more discomfort or fatigue than those for the optimum 3D contents, which resulting in the greater b wave activity for those watching the distorted 3D contents. In conclusion, these results confirm that electroencephalogram (EEG) analysis can be used as a tool for objective evaluation of 3D contents using autosteroscopic display with lenticular lens type.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.8
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• pp.385-392
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• 2016

Market analysis for a business plain is required for the success in the modern world. Most important part in this analysis is pedestrian traffic counting. A traditional way for this is counting it in person. However, it causes high labor costs and mistakes. This paper proposes an automatic algorithm to measure the pedestrian traffic count using images with webcam. The proposed algorithm is composed of two parts: pedestrian area detection and movement tracking. In pedestrian area detection, moving blobs are extracted and pedestrian areas are detected using HoG features and Adaboost algorithm. In movement tracking, multi-level matching and false positive removal are applied to track pedestrian areas and count the pedestrian traffic. Multi-level matching is composed of 3 steps: (1) the similarity calculation between HoG area, (2) the similarity calculation of the estimated position with Kalman filtering, and (3) the similarity calculation of moving blobs in the pedestrian area detection. False positive removal is to remove invalid pedestrian area. To analyze the performance of the proposed algorithm, a comparison is performed with the previous human area detection and tracking algorithm. The proposed algorithm achieves 83.6% accuracy in the pedestrian traffic counting, which is better than the previous algorithm over 11%.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.329-334
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• 2014

In this study, a new method that automatically segments trabecular bone for its morphological analysis using micro-computed tomography imaging was proposed. In the proposed method, the bone region was extracted using a threshold value, and the outer boundary of the bone was detected. The sphere of maximum size with the corresponding voxel as the center was obtained by applying the sphere-fitting method to each voxel of the bone region. If this sphere includes the outer boundary of the bone, the voxels included in the sphere are classified as cortical bone; otherwise, they are classified as trabecular bone. The proposed method was applied to images of the distal femurs of 15 mice, and comparative experiments, with results manually divided by a person, were performed. Four morphological parameters-BV/TV, Tb.Th, Tb.Sp, and Tb.N-for the segmented trabecular bone were measured. The results were compared by regression analysis and the Bland-Altman method; BV/TV, Tb.Th, Tb.Sp, and Tb.N were all in the credible range. In addition, not only can the sphere-fitting method be simply implemented, but trabecular bone can also be divided precisely by using the three-dimensional information.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.653-662
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• 2016

This paper describes a test case generation algorithm for Simulink/Stateflow models based on the Rapidly exploring Random Tree (RRT) algorithm that has been successfully applied to path finding. An important factor influencing the performance of the RRT algorithm is the metric used for calculating the distance between the nodes in the RRT space. Since a test case for a Simulink/Stateflow (SL/SF) model is an input sequence to check a specific condition (called a test target in this paper) at a specific status of the model, it is necessary to drive the model to the status before checking the condition. A status maps to a node of the RRT. It is usually necessary to check various conditions at a specific status. For example, when the specific status represents an SL/SF model state from which multiple transitions are made, we must check multiple conditions to measure the transition coverage. We propose a unique distance calculation metric, based on the observation that the test targets are gathered around some specific status such as an SL/SF state, named key nodes in this paper. The proposed metric increases the probability that an RRT is extended from key nodes by imposing penalties to non-key nodes. A test case generation algorithm utilizing the proposed metric is proposed. Three models of Electrical Control Units (ECUs) embedded in a commercial vehicle are used for the performance evaluation. The performances are evaluated in terms of penalties and compared with those of the algorithm using a typical RRT algorithm.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.315-320
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• 2017

Estimating the correct pose of augmented objects on the real camera view efficiently is one of the most important questions in image tracking area. In computer vision, Homography is used for camera pose estimation in augmented reality system with markerless. To estimating Homography, several algorithm like SURF features which extracted from images are used. Based on extracted features, Homography is estimated. For this purpose, RANSAC algorithm is well used to estimate homography and DCS-RANSAC algorithm is researched which apply constraints dynamically based on Constraint Satisfaction Problem to improve performance. In DCS-RANSAC, however, the dataset is based on pattern of feature distribution of images manually, so this algorithm cannot classify the input image, pattern of feature distribution is not recognized in DCS-RANSAC algorithm, which lead to reduce it's performance. To improve this problem, we suggest the KCS-RANSAC algorithm using K-means clustering in CS-RANSAC to cluster the images automatically based on pattern of feature distribution and apply constraints to each image groups. The suggested algorithm cluster the images automatically and apply the constraints to each clustered image groups. The experiment result shows that our KCS-RANSAC algorithm outperformed the DCS-RANSAC algorithm in terms of speed, accuracy, and inlier rate.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.10
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• pp.377-382
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• 2018

This study deals with internal state and tissue density analysis methods for red ginseng grade determination. For internal measurement of red ginseng, there have been various studies on nondestructive testing methods since the 1990s, It was difficult to grasp the most important inner hole and inside whites in the grading. So in this study, we developed a closed capturing device for infra-red illumination environment, and developed an internal measurement system that can detect the presence and diameter of inner hole and inside whites. Made devices consisted of infrared lights with a high transmission rate of red ginseng in 920 nanometer wave band, a infra-red camera and a Y axis actuator with a red ginseng automatically controlled focus on the camera. The proposed algorithm performs an auto-focus system on the Y-axis actuator to automatically adjust the sharp focus of the object according to the size and thickness. Then red ginseng is rotated $360^{\circ}$ at $1^{\circ}$ intervals and 360 total images are acquired, and reconstructed as a sinogram through Radon transform and Back-projection algorithm was performed to acquire internal images of red ginseng. As a result of the algorithm, it was possible to acquire internal cross-sectional image regardless of the thickness and shape of red ginseng. In the future, if more than 10,000 different shapes and sizes of red ginseng internal cross-sectional image are acquired and the classification criterion is applied, it can be used as a reliable automated ginseng grade automatic measurement method.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.12
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• pp.499-506
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• 2019

An intelligent robot should decide its behavior accordingly to the dynamic changes in the environment and user's requirements by evaluating options to choose the best one for the current situation. Many intelligent robot systems that use the Procedural Reasoning System (PRS) accomplishes such task management functions by defining the priority functions in the task model and evaluating the priority functions of the applicable tasks in the current situation. The priority functions, however, are defined locally inside of the plan, which exhibits limitation for the tasks for multi-domain services because global contexts for overall prioritization are hard to be expressed in the local priority functions. Furthermore, since the prioritization functions are not defined as an explicit module, reuse or extension of the them for general context is limited. In order to remove such limitations, we propose a policy-based meta-planning for general task management for multi-domain services, which provides the ability to explicitly define the utility of a task in the meta-planning process and thus the ability to evaluate task priorities for general context combining the modular priority functions. The ontological specification of the model also enhances the scalability of the policy model. In the experiments, adaptive behavior of a robot according to the policy model are confirmed by observing the appropriate tasks are selected in dynamic service environments.