• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.403-403
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• 2000

Generally estimation of driving direction uses the way which uses lane detection and vanishing point in autonomous-driving system. Especially we use Sub-window for decreasing Process time when we detect lane, but fixed sub-window can not detect lane because of some factors in road image. So we suggest algorithm using one-dimension line scan method to detect an exact position of lane.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.9-14
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• 1994

The modern CNC machine require increasingly an exact monitoring and control of cutting process. They are to make final taret which construct full automation factories as unmanned system. In this study, we decided that we develop new techique to monitor and detect tool breakage on the machining operation using face milling machine with multi-point throwaway tips. The technology in which the tool is illuminated by an beam of Laser is used by image of tool fracture through CCD camera.

• Journal of Biosystems Engineering
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• v.26 no.6
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• pp.545-552
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• 2001

Nondestructive methods such as ultrasonic and magnetic resonance imaging systems have many advantages but still much expensive. And they do not give exact color information and may miss some details. If it is allowed to destruct a biological object to obtain interior and exterior informations, 3D image visualization model from a series of sliced sectional images gives more useful information with relatively low cost. In this paper, a PC based automatic 3D visualization system is presented. The system is composed of three modules. The first module is the handling and image acquisition module. The handling module feeds and slices a cylindrical shape paraffin, which holds a biological object inside the paraffin. And the paraffin is kept being solid by cooling while being handled. The image acquisition modulo captures the sectional image of the object merged into the paraffin consecutively. The second one is the system control and interface module, which controls actuators for feeding, slicing, and image capturing. And the last one is the image processing and visualization module, which processes a series of acquired sectional images and generates a 3D volumetric model. To verify the condition for the uniform slicing, normal directional forces of the cutting edge according to the various cutting angles were measured using a strain gauge and the amount of the sliced chips were weighed and analyzed. Once the 3D model was constructed on the computer, user could manipulate it with various transformation methods such as translation, rotation, and scaling including arbitrary sectional view.

• Journal of Korea Multimedia Society
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• v.10 no.7
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• pp.923-933
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• 2007

In this paper, we present a method for performance enhancement of the marker detection system by using SVM(Support Vector Machine) and LDA(Linear Discriminant Analysis). It converts the input image to a binary image and extracts contours of objects in the binary image. After that, it approximates the contours to a list of line segments. It finds quadrangle by using geometrical features which are extracted from the approximated line segments. It normalizes the shape of extracted quadrangle into exact squares by using the warping technique and scale transformation. It extracts feature vectors from the square image by using principal component analysis. It then checks if the square image is a marker image or a non-marker image by using a SVM classifier. After that, it computes feature vectors by using LDA for the extracted marker images. And it calculates the distance between feature vector of input marker image and those of standard markers. Finally, it recognizes the marker by using minimum distance method. Experimental results show that the proposed method achieves enhancement of recognition rate with smaller feature vectors by using LDA and it can decrease false detection errors by using SVM.

• The KIPS Transactions:PartB
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• v.16B no.3
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• pp.195-202
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• 2009

In this paper, we propose the regions segmentation method of the white matter and the gray matter for brain MR image by using the ant colony optimization algorithm. Ant Colony Optimization (ACO) is a new meta heuristics algorithm to solve hard combinatorial optimization problem. This algorithm finds the expected pixel for image as the real ant finds the food from nest to food source. Then ants deposit pheromone on the pixels, and the pheromone will affect the motion of next ants. At each iteration step, ants will change their positions in the image according to the transition rule. Finally, we can obtain the segmentation results through analyzing the pheromone distribution in the image. We compared the proposed method with other threshold methods, viz. the Otsu' method, the genetic algorithm, the fuzzy method, and the original ant colony optimization algorithm. From comparison results, the proposed method is more exact than other threshold methods for the segmentation of specific region structures in MR brain image.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.3
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• pp.262-268
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• 2010

In this paper, this study restores the distorted image to its original image by compensating for the distortion of image from a fixed-focus camera lens. The various developments and applications of the imaging devices and the image sensors used in a wide range of industries and expanded use, but due to the needs of the small size and light weight of the camera, the distortion from acquiring images of the distorted curvature of the lens tends to affect many. In particular, the three-dimensional imaging camera, each different distortion of left and right lens cause the degradation of three-dimensional sensitivity and left-right image distortion ratio. we approached the way of generalizing the approximate equations to restore each part of left-right camera images to the coordinators of the original images. The adaptive Neuro-Fuzzy Inference System is configured for it. This system is divided from each membership function and is inferred by 1st order Sugeno Fuzzy model. The result is that the compensated images close to the left, right original images. Using low-cost and compact imaging lens by which also determine the exact three-dimensional image-sensing capabilities and will be able to expect from this study.

• Journal of Korea Multimedia Society
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• v.18 no.1
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• pp.25-34
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• 2015

Recently, in distribution market, demand for electronic shelf label system is increasing gradually to provide the accurate price immediately and detailed product information to consumers and reduce operation costs. Most of electronic shelf label system companies develop the full-graphic display device to display a wide variety of product information as well as the exact price. Our system had introduced Go-Back-N retransmission method in the early. However, we encountered performance problems that it delayed updating of the electronic shelf label system and exhausted the battery life time. Proposed adaptive image retransmission technique based on the selective scheme is that tags of electronic shelf label system recognize idle time of transmission cycle and require partial image retransmission to sever by itself. As a result, it can acquire much more opportunities of partial image retransmission within the same period and increase reception rate of full image for each tags. The experimental result shows that adaptive image retransmission technique's reception rate of full image for each tags is approximately 4% higher than existing previous works. And total battery life time increases 30 hours because tag reduce wake-up time as it receive only lost data instead of whole data.

• Journal of the Korean Society of Radiology
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• v.14 no.2
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• pp.111-120
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• 2020

Research should be actively conducted for the ability of X-ray equipment and Retrospective image analysis of X-ray equipment used in hospitals. Retrospective image analysis of X-ray machines, CT and MRI of radiology and medical equipment has been actively conducted. However, image quality measurement using angiography equipment of angiography room is mostly measured with phantom, and image quality measurement on image after being taken by actual patient is insufficient and researches on accurate image quality measurement method are remarkable. It is in short supply. Therefore, through this study, the researcher devised a method to measure the image quality of the acquired image after coronary angiography, and to provide a high quality image to the operator. The equipment and programs used were angiographic examination equipment (Axiom Artis Zee Ceiling) and Image J program. Subjects were images automatically saved in PACS program after coronary angiography.For image quality measurement, selected the AP Caudal 30° image that show the LCA vessel well and the LAO 30° image that show the RCA vessel well during the coronary angiography. In order to measure the background and ROI of the selected image by selecting an image, a criterion on how to find and measure a section where the overlap of the shadow, such as blood vessel, liver and lung is minimized, is presented. In conclusion, there is no exact standard for analyzing an image quality measurement method of angiography image. Therefore, in order to provide quality images to the practistioners, not only the technicians of the equipment but also the users who actually use them should become researchers and conduct research on image quality measurement in various ways. Thus, it is expected to provide excellent images to patients.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.214-217
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• 2000

Many researches have been performed for human recognition and coding schemes recently. For this situation, we propose an automatic facial feature extraction algorithm. There are two main steps: the face region evaluation from original background image such as office, and the facial feature extraction from the evaluated face region. In the face evaluation, Genetic Algorithm is adopted to search face region in background easily such as office and household in the first step, and Template Matching Method is used to extract the facial feature in the second step. We can extract facial feature more fast and exact by using over the proposed Algorithm.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.619-622
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• 1999

This paper describes a new semi-automatic segmentation algorithm based on color information. Semi-automatic segmentation mainly consists of intra-frame segmentation and inter-frame segmentation. While intra-frame segmentation extracts video objects of interest from boundary information provided by the user and intensity information of the image, inter-frame segmentation partitions the image into the video objects and background by tracking the motion of video objects. For inter-frame segmentation, color information (Y, Cb and Cr) of the current frame can be used efficiently in order to find the exact boundary of the video objects. In this paper we propose a new region growing algorithm which can maximize the ability of region differentiation, while preserving features of each color component.