• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.76-83
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• 2023

Recently, the development of computer vision with deep learning has made object detection using images applicable to diverse fields, such as medical care, manufacturing, and transportation. The manufacturing industry is saving time and money by applying computer vision technology to detect defects or issues that may occur during the manufacturing and inspection process. Annotations of collected images and their location information are required for computer vision technology. However, manually labeling large amounts of images is time-consuming, expensive, and can vary among workers, which may affect annotation quality and cause inaccurate performance. This paper proposes a process that can automatically collect annotations and location information for images using eXplainable AI, without manual annotation. If applied to the manufacturing industry, this process is thought to save the time and cost required for image annotation collection and collect relatively high-quality annotation information.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.5
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• pp.312-321
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• 2003

In this paper, we implement robot which are ability to recognize obstacles and moving automatically to destination. we present two results in this paper; hardware implementation of image processing board and software implementation of visual feedback algorithm for a self-controlled robot. In the first part, the mobile robot depends on commands from a control board which is doing image processing part. We have studied the self controlled mobile robot system equipped with a CCD camera for a long time. This robot system consists of a image processing board implemented with DSPs, a stepping motor, a CCD camera. We will propose an algorithm in which commands are delivered for the robot to move in the planned path. The distance that the robot is supposed to move is calculated on the basis of the absolute coordinate and the coordinate of the target spot. And the image signal acquired by the CCD camera mounted on the robot is captured at every sampling time in order for the robot to automatically avoid the obstacle and finally to reach the destination. The image processing board consists of DSP (TMS320VC33), ADV611, SAA7111, ADV7l76A, CPLD(EPM7256ATC144), and SRAM memories. In the second part, the visual feedback control has two types of vision algorithms: obstacle avoidance and path planning. The first algorithm is cell, part of the image divided by blob analysis. We will do image preprocessing to improve the input image. This image preprocessing consists of filtering, edge detection, NOR converting, and threshold-ing. This major image processing includes labeling, segmentation, and pixel density calculation. In the second algorithm, after an image frame went through preprocessing (edge detection, converting, thresholding), the histogram is measured vertically (the y-axis direction). Then, the binary histogram of the image shows waveforms with only black and white variations. Here we use the fact that since obstacles appear as sectional diagrams as if they were walls, there is no variation in the histogram. The intensities of the line histogram are measured as vertically at intervals of 20 pixels. So, we can find uniform and nonuniform regions of the waveforms and define the period of uniform waveforms as an obstacle region. We can see that the algorithm is very useful for the robot to move avoiding obstacles.

• The Korean Journal of Nuclear Medicine
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• v.34 no.4
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• pp.344-352
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• 2000

Purpose: Re-188-Hydroxyethylidene diphosphonate (HEDP) is a new cost-effective agent for systemic radioisotope therapy of metastatic bone pain. We investigated the influence of carrier for labeling and biodistribution of Re-188-HEDP using HEDP kit with or without carrier ($KReO_4$). Materials and Methods: The kits (HEDP 15 mg, gentisic acid 4 mg and $SnCl_2.2H_2O_2$ 4.5 mg) with or without carrier ($KReO_4$ 0.1 mg) were labeled with Re-188 solution, made available from an in-house generator by boiling for 15 min. We compared the labeling efficiency and stability of carrier-added and carrier-free preparations of Re-188-HEDP Biodistribution and imaging studies of each preparation were performed in ICR mice ($1.85{\sim}3.7MBq/0.1ml$) and SD rats ($74.1{\sim}85.2MBq/0.5ml$). Results: The carrier-added preparation showed high labeling efficiency (95% at pH 5) and high stability in serum (88%, 3 hr). However, the carrier-free preparation showed low labeling efficiency (59% at pH 5) and low stability (43%, 3 hr). The carrier-added preparation showed high uptake in bone and low uptake in stomach and kidneys. However, the carrier-free preparation showed lower uptake in bone and higher uptake in both stomach and kidneys, which is supposed to be due to released perrhenate. The carrier-added preparation also showed better images with higher skeletal accumulation, lower uptake in other organs and lower soft tissue uptake than the carrier-free preparation. Conclusion: The results of these studies clearly demonstrate that addition of carrier perrhenate is required for high labeling efficiency, stability, bone uptake and good image quality of Re-188-HEDP.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.31-39
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• 2010

The paper proposes the median filter based Retinex algorithm to detect the lanes in a foggy image. Whether an input image is foggy or not is determined by analyzing the histogram in the pre-defined ROI(Region of Interest). If the image is determined as a foggy one, then it is improved by the median filter based Retinex algorithm. By replacing the Gaussian filter by the median filter in the Retinex algorithm, the processing time can be reduced and the lane features can be detected more robustly. Once the enhanced image is acquired, the binarization based on multi-threshold and the labeling operations are applied. Finally, it detects the lane information using the size and direction parameters of the detected lane features. The proposed algorithm has been evaluated by using various foggy images collected on different road conditions to prove that it detects lanes more robustly in most cases than the conventional methods.

• The Korean Journal of Nuclear Medicine
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• v.30 no.3
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• pp.367-371
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• 1996

The $MAG_3$ is a tubular excreting radiopharmaceutical for renal image. We synthesized benzoyl $MAG_3\;(Bz-MAG_3)$ and made a kit for labeling with $^{99m}Tc$. We checked the labeling efficieny of $^{99m}Tc$ labeled $MAG_3$ and biodistribution. Labeling efficieny was checked by TLC-SG (acetonitrile/$H_2O$=2/1). After injecting of 1 mCi of $^{99m}Tc-MAG_3$ to ICR-mice, $T_{max}(min),\;T_{1/2}(min)$ were obtained in the renogram. Sequential images (30sec, 2min, 5min, 10min, 15min, 20min) of $^{99m}Tc-MAG_3$ were compared with those of commercial $^{99m}Tc$-DTPA (Du Pont Merck Pharmaceutical Co.) kit. 1) The $R_f$ value of synthesized $^{99m}Tc-MAG_3$ was 0.78 and labeling efficiency was $97.5{\pm}1.9%$ (n=10). 2) The dynamic images of the $^{99m}Tc-MAG_3$ were better than those of the $^{99m}Tc$-DTPA. 3) The $T_{max}(min.)$ and $T_{1/2}(min.)$ of $^{99m}Tc-MAG_3$ (n=10) were $1.5{\pm}0.5$ (left), $1.4{\pm}0.4$ (right), and $4.3{\pm}1.4$ (left), $4.8{\pm}2.0$ (right), respectively. The $T_{max}(min.)$ and $T_{1/2}(min.)$ of $^{99m}Tc$-DTPA (n=7) were $2.7{\pm}1.6$ (left), $2.7{\pm}1.6$ (right), and $3.8{\pm}1.7$ (left), $4.5{\pm}2.7$ (right), respectively. The quaility of image and labeling efficiency of the synthesized $Bz-MAG_3$ kit were excellent, that it was supposed to be used in routine clinical work.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.5
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• pp.734-739
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• 2018

Fingerprint recognition and iris recognition, which are one of the biometric methods, are easily influenced by external factors such as sunlight. Recently, finger vein recognition is used as a method utilizing internal features. However, for accurate finger vein recognition, it is important to clearly separate vein and background regions. However, it is difficult to separate the vein region and background region due to the abnormalized illumination, and a method of separating the vein region and the background region after normalized the illumination of the input image has been proposed. In this paper, we proposed a method to enhance the quality improvement and improve the processing time compared to the existing finger vein recognition system binarization and labeling method of the image including the image stretching process based on the existing illumination normalization method.

• Journal of Biosystems Engineering
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• v.35 no.4
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• pp.257-261
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• 2010

Surface energy is the principal factor of anti-condensation. High surface energy appears hydrophilic itself and low surface energy represents hydrophobic itself. The contact angle is widely being used for measurement of surface energy of materials, evaluation of coating performances, measurement of wettability, and so on. However, the existing contact angle measuring system is so expensive for purchasing and complicated, so it takes a lot of time and money to use. This study was conducted to develop the algorithm for evaluating hydrophilic performance through measuring the contact angle of water droplet automatically, and fabricate relatively simple measuring system using a low-cost monochrome camera and image processing. A constant amount of water was firstly allocated on a slide by a micropipette, and then the image of water droplet was captured by monochrome digital camera and sent to a computer. The image was binarized and then reduced noises by labeling. Finally, the contact angle of water droplet was computed by using three points (left, right, and top coordinates), simple linear mathematics, and trigonometric function. The experimental results demonstrated the accuracy and reproducibility of the developed system showing less deviations and deviation ratio.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.591-597
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• 2012

Medical device performance has been advanced while images are expected to be acquired with further higher quality and pertinent applicability as images have been increasing in importance in analyzing major organs. Recent high frequency of image processing by MATLAB in image analysis area accounts for the intent of this study to segment pulmonary vessels by means of MATLAB. This study is to consist of 3 phases including pulmonary region segmentation, pulmonary vessel segmentation and three dimensional connectivity assessment, in which vessel was segmented, using threshold level, from the pulmonary region segmented, vessel thickness was measured as two dimensional refining process and three dimensional connectivity was assessed as three dimensional refining process. It is expected that MATLAB-based image processing should contribute to diversity and reliability of medical image processing and that the study results may lay a foundation for chest CT images-related researches.

• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.41-46
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• 2010

In this paper, we propose a detection method of reduced computational complexity aimed at separating the moving objects from the background in a generic video sequence. In generally, indoor environments, it is difficult to accurately detect the object because environmental factors, such as lighting changes, shadows, reflections on the floor. First, the background image to detect an object is created. If an object exists in video, on a previously created background images for similarity comparison between the current input image and to detect objects through several operations to generate a mixture image. Mixed-use video and video inputs to detect objects. To complement the objects detected through the labeling process to remove noise components and then apply the technique of morphology complements the object area. Environment variable such as, lighting changes and shadows, to the strength of the object is detected. In this paper, we proposed that environmental factors, such as lighting changes, shadows, reflections on the floor, including the system uses mixture images. Therefore, the existing system more effectively than the object region is detected.

• Journal of Internet of Things and Convergence
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• v.6 no.2
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• pp.37-43
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• 2020

The paper proposed the method of calculating the latest approach angle that can reliably recognize multiple laser images even with the change in separation distance between screen and laser launch device. This method recognizes the angle of the laser pattern angle by using the distance of the laser pattern angle, and the angle extraction of the laser detects the laser image from the acquired image using the labeling algorithm, and performs the huff conversion to extract the angle of the straight line. The distance of the reference angle and angle of the laser image extracted using Euclidean distance among similarity scales is calculated, and the furnace is recognized using the calculated distance result value. Experiments with changing the separation distance to "200 cm to 400 cm" showed 100% recognition of individual strands at all separation distances. The experiment confirmed the reliability of the proposed method.