• Journal of the Korea Society of Computer and Information
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• v.18 no.4
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• pp.13-18
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• 2013

Panorama picturing is an elongated photographing technique that connects images with rotating and moving multiple images horizontally that are partly overlapped. However, for hand-operated photographs, it is difficult to adjust overlapped parts because of tilted angles. There has been a study comparing adjacent pictures using labeling technique but it was time-consuming and had angle dissonant cases in nature. In this paper, we propose a less time-consuming paranoiac scene reconstruction method. Our method is also based on labeling-and-comparing technique but uses only 1/3 of it. Then, if there exists angle dissonance, it tries to find characteristic points by SURF algorithm and adjusts them with homography. The efficacy of this method is experimentally verified by experiments using various images

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.144-152
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• 2007

We propose a 3D modeling method for surface inspection of non-linear moving object. The laser lines reflect the surface curvature. We can acquire 3D surface information by analyzing projected laser lines on object. ill this paper, we use multi-line laser to make use of robust of single stripe method and high speed of single frame. Binarization and channel edge extraction method were used for robust laser line extraction. A new labeling method was used for laser line labeling. We acquired sink information between each 3D reconstructed frame by feature point matching, and registered each frame to one whole image. We verified the superiority of proposed method by applying it to container damage inspection system.

• The Korean Journal of Nuclear Medicine
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• v.22 no.2
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• pp.193-197
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• 1988

Measurement of gastric emptying rate has been performed by a variety of techniques. Nuclear medicine method is a major advance in the quantitative evaluation of gastric function and also of pharmacologic intervention. Normal gastric emptying rate was measured in 48 healthy volunteers using live chicken liver labeled with $^{99m}Tc-Tin$ Colloid as a solid phase marker. In vitro studies were performed to evaluate the labeling efficiency and stability in hydrochloric acid and in human gastric juice of intracellularly labeled chicken liver. Anterior image counts only were compared with the geometric mean of anterior and posterior counts in 12 healthy volunteers who were studied by both anterior count and posterior count. The results were as follows: 1) The labeling efficiency in gastric juice and hydrochloric acid were $95.5{\pm}1.23%,\;95.7{\pm}1.15%$, respectively. 2) Half gastric emptying time by anterior count only was $126{\pm}21$ minutes 3) Although standard deviation of geometric mean method was smaller than anterior count method, gastric emptying curves from both method were similar. In daily practice, anterior count method may be useful alternative to geometric mean method in evaluation of gastric emptying rate.

• Journal of Korean Neurosurgical Society
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• v.49 no.1
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• pp.26-30
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• 2011

Objective: The primary objective of this study was to perform a retrospective evaluation of the radiological and pathological features influencing the formation of peritumoral brain edema (PTBE) in meningiomas. Methods: The magnetic resonance imaging (MRI) and pathology data for 86 patients with meningiomas, who underwent surgery at our institution between September 2003 and March 2009, were examined. We evaluated predictive factors related to peritumoral edema including gender, tumor volume, shape of tumor margin, presence of arachnoid plane, the signal intensity (SI) of the tumor in T2-weighted image (T2WI), the WHO histological classification (GI, GII/GIII) and the Ki-67 antigen labeling index (LI). The edema-tumor volume ratio was calculated as the edema index (EI) and was used to evaluate peritumoral edema. Results: Gender (p=0.809) and pathological finding (p=0.084) were not statistically significantly associated with peritumoral edema by univariate analysis. Tumor volume was not correlated with the volume of peritumoral edema. By univariate analysis, three radiological features, and one pathological finding, were associated with PTBE of statistical significance: shape of tumor margin (p=0.001), presence of arachnoid plane (p=0.001), high SI of tumor in T2WI (p=0.001), and Ki-67 antigen LI (p=0.049). These results suggest that irregular tumor margins, hyperintensity in T2WI, absence of arachnoid plane on the MRI, and high Ki-67 LI can be important predictive factors that influence the formation of peritumoral edema in meningiomas. By multivariate analysis, only SI of the tumor in T2WI was statistically significantly associated with peritumoral edema. Conclusion: Results of this study indicate that irregular tumor margin, hyperintensity in T2WI, absence of arachnoid plane on the MRI, and high Ki-67 LI may be important predictive factors influencing the formation of peritumoral edema in meningiomas.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.89-95
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• 2015

In this paper, we propose a real-time two-dimensional bar code detection system even at long range using a vision technique. We first perform short-range detection, and then long-range detection if the short-range detection is not successful. First, edge map generation, image binarization, and connect component labeling (CCL) are performed in order to select a region of interest (ROI). After interpolating the selected ROI using bilinear interpolation, a location symbol pattern is detected as the same as for short-range detection. Finally, the symbol pattern is arranged by applying inverse perspective transformation to localize bar codes. Experimental results demonstrate that the proposed system successfully detects bar codes at two or three times longer distance than existing ones even at indoor environment.

• Journal of Digital Contents Society
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• v.16 no.1
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• pp.157-164
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• 2015

The existing input device is limited to keyboard and mouse. However, recently new type of input device has been developed in response to requests from users. To reflect this trend we propose the new type of input device that gives instruction as analyzing the hand motion of image without special device. After binarizing the skin color area using Cam-Shift method and tracking, it recognizes the hand motion by inputting the finger areas and the angles from the palm center point, which are separated through labeling, into four cardinal directions and counting them. In cases when specific background was not set and without gloves, the recognition rate remained approximately at 75 percent. However, when specific background was set and the person wore red gloves, the recognition rate increased to 90.2 percent due to reduction in noise.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.3
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• pp.237-246
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• 2001

A high speed context-free marker-controlled and minima imposition-free watershed transform is proposed for efficient multi-object detection and segmentation from a complex background. The context-free markers are extracted from a complex backgrounded multi-object image using a noise tolerant attention operator. These make marker-controlled watershed possible for the over-segmentation reduction without region merging. The proposed method presents a marker-constrained labeling that can speed up the segmentation of a marker-controlled watershed transform by eliminating the necessity of the minima imposition. Simulation results show that the proposed method can efficiently detects and segments multiple objects from a complex background while reducing over- segmentation and the computation time.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.718-723
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• 2011

In this paper, we propose a visual multi-touch air input device using vision cameras. The implemented device provides a barehanded interface which copes with the multi-touch operation. The proposed device is easy to apply to the real-time systems because of its low computational load and is cheaper than the existing methods using glove data or 3-dimensional data because any additional equipment is not required. To do this, first, we propose an image processing algorithm based on the HSV color model and the labeling from obtained images. Also, to improve the accuracy of the recognition of hand gestures, we propose a motion recognition algorithm based on the geometric feature points, the skeleton model, and the Kalman filter. Finally, the experiments show that the proposed device is applicable to remote controllers for video games, smart TVs and any computer applications.

• Journal of IKEEE
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• v.24 no.4
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• pp.1141-1147
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• 2020

The hornet species are so similar in shape that they are difficult for non-experts to classify, and because the size of the objects is small and move fast, it is more difficult to detect and classify the species in real time. In this paper, we developed a system that classifies hornets species in real time based on a deep learning algorithm using a boundary box. In order to minimize the background area included in the bounding box when labeling the training image, we propose a method of selecting only the head and body of the hornet. It also experimentally compares existing boundary box-based object recognition algorithms to find the best algorithms that can detect wasps in real time and classify their species. As a result of the experiment, when the mish function was applied as the activation function of the convolution layer and the hornet images were tested using the YOLOv4 model with the Spatial Attention Module (SAM) applied before the object detection block, the average precision was 97.89% and the average recall was 98.69%.

• Journal of Platform Technology
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• v.11 no.3
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• pp.56-67
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• 2023

Recently, de-identification of personal information, which has been a long-cherished desire of the data-based industry, was revised and specified in August 2020. It became the foundation for activating data called crude oil[2] in the fourth industrial era in the industrial field. However, some people are concerned about the infringement of the basic rights of the data subject[3]. Accordingly, a development study was conducted on the Batch De-Identification Tool, a personal information de-identification automation tool. In this study, first, we developed an image labeling tool to label human faces (eyes, nose, mouth) and car license plates of various resolutions to build data for training. Second, an object recognition model was trained to run the object recognition module to perform de-identification of personal information. The automated personal information de-identification tool developed as a result of this research shows the possibility of proactively eliminating privacy violations through online services. These results suggest possibilities for data-based industries to maximize the value of data while balancing privacy and utilization.