• Journal of Biomedical Engineering Research
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• v.24 no.2
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• pp.91-97
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• 2003

The Propose of this paper is hierarchical detection method for the optic disc in fundus image. We detected the optic disc boundary by using the Prior information. It is based on the anatomical knowledge of fundus which are the vessel information. the image complexity. and etc. The whole method can be divided into three stages . First, we selected the region of interest(ROI) which included optic disc region. This is used to calculate location and size of the optic disc which are prior knowledge to simplify image preprocessing. And then. we divided the fundus image into numberous regions with watershed algorithm and detected intial boundary of the optic disc by reducing the number of the separated regions in ROI. Finally, we have searching the defective parts of boundary as a result of serious vessel interference in order to detect the accurate boundary of optic disc and we have removing and interpolating them.

• Journal of radiological science and technology
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• v.31 no.1
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• pp.61-69
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• 2008

Diagnosis of breast ultrasound is better than mammography in the early detection of breast cancer, but, it is difficult to detect microcalcification. We studied on detection for calcification of breast tissue using acoustic resonance and power doppler with 7.5 MHz linear probe in breast ultrasound. We first constructed breast tissue phantom made of gelatin and saw breast, and then observed calcification by the change of external vibration. Calcification injected breast tissue phantom visualized the difference for brightness and region of color in ROI regions of power doppler. Acoustic resonance almost never visualized in low frequency regions, plateau constituted in about 300-400 Hz and colors vanished according to the increase of frequency.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.5
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• pp.944-951
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• 2009

In this paper, we use image processing algorithms to detect the defects existed on a welding area automatically. It is difficult to detect the welding defects because it is sensitive to lights and has irregular patterns. For this reason, images are captured with 2 kinds of illumination condition, and are processed by 2 different algorithms for each image. The first algorithm separates some ROI's from the captured image and compares the similarity of intensity between each divided region. The second algorithm extracts boundary information from the processed image by the first algorithm, and calculates the length of boundary, curvature and base line area based on boundary information. The proposed method showed high performance in detection and classification of defects.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.275-280
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• 2004

In this paper, we propose automatic subtraction radiography algorithms to overcome conventional subtraction radiography's defects by applying image processing technique. In order to reach these goals, this paper suggests the image alignment method that is necessary for getting subtraction image and ROI(Region Of Interest) focused on a selection method using the structure characteristics in target images. Therefore, we use these methods because they give accurary, consistency and objective information or data to results. According to the results, easily and visually we can identify fine difference int the affected parts wether they have problems or not.

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.133-139
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• 2004

In this paper. we propose a medical image processing method for detection of periodontal disease by geometric analysis on dental digital radiography. This paper proposes the method of an automatic image alignment and detection of minute changes, to overcome defects in the conventional subtraction radiography by image processing technique, that is necessary for getting subtraction image and ROI(Region Of Interest) focused on a selection method using the geometric features in target images. Therefore, we use these methods because they give accuracy, consistency and objective information or data to results. In result, easily and visually we can identify minute differences in the affected parts whether they have problems or not, and using application system.

• Journal of Sensor Science and Technology
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• v.27 no.4
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• pp.216-220
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• 2018

In this paper, we present visual sensing techniques that can be used to teach a robot using a laser pointer. The light spot of an off-the-shelf laser pointer is detected and its movement is tracked on consecutive images of a camera. The three-dimensional position of the spot is calculated using stereo cameras. The light spot on the image is detected based on its color, brightness, and shape. The detection results in a binary image, and morphological processing steps are performed on the image to refine the detection. The movement of the laser spot is measured using two methods. The first is a simple method of specifying the region of interest (ROI) centered at the current location of the light spot and finding the spot within the ROI on the next image. It is assumed that the movement of the spot is not large on two consecutive images. The second method is using a Kalman filter, which has been widely employed in trajectory estimation problems. In our simulation study of various cases, Kalman filtering shows better results mostly. However, there is a problem of fitting the system model of the filter to the pattern of the spot movement.

• Journal of Korea Multimedia Society
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• v.10 no.2
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• pp.218-225
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• 2007

This paper presents a technique to detect a document skew that often occurs during document scanning. To correct a skewed document is essential for automatic processing system including character segmentation, character recognition and so on. The proposed algorithm can detect a skew angle exactly by searching characters baselines that have slant information of the document within a candidated area. To reduce processing time, we resized the image small and then established a ROI (region of interest) by morphology operations and connected components analysis. We compared our method with the existing method based on morphology operations and proved correctness and efficiency of the proposed algorithm through experiments and analysis with various kind of document images.

• Journal of Practical Engineering Education
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• v.13 no.3
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• pp.491-496
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• 2021

In this thesis, we intend to use CCTVs installed in existing parking lots to understand the current status of parking lots and provide real-time information to users through Android applications. It describes how to set the ROI in the parking area using YOLO V3 and how to provide the number of vacancies that change in real time through the set ROI, and describes how to link CCTV-server-user using IMAGE ZMQ and FIREBASE. The user can know the real-time situation of the parking lot near the destination before arriving through the application and can come up with various measures accordingly.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.3
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• pp.249-255
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• 2017

The finger vein recognition technology is a method to acquire a finger vein image by illuminating infrared light to the finger and to authenticate a person through processes such as feature extraction and matching. In order to recognize a finger vein, a 2D mask-based two-dimensional convolution method can be used to detect a finger edge but it takes too much computation time when it is applied to a low cost micro-processor or micro-controller. To solve this problem and improve the recognition rate, this study proposed an extraction method for the region of interest based on virtual core points and moving average filtering based on the threshold and absolute value of difference between pixels without using 2D convolution and 2D masks. To evaluate the performance of the proposed method, 600 finger vein images were used to compare the edge extraction speed and accuracy of ROI extraction between the proposed method and existing methods. The comparison result showed that a processing speed of the proposed method was at least twice faster than those of the existing methods and the accuracy of ROI extraction was 6% higher than those of the existing methods. From the results, the proposed method is expected to have high processing speed and high recognition rate when it is applied to inexpensive microprocessors.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.135-136
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• 2017

When driving at night time environment, the whole body of transports does not visible to us. Due to lack of light conditions, there are only two options, which is clearly visible their taillights and break lights. To improve the recognition correctness of vehicle detection, we present an approach to vehicle detection and tracking using finding contour of the object on binary image at night time. Bilateral filtering is used to make more clearly on threshold part. To remove unexpected small noises used morphological opening. In verification stage, paired tail lights are tracked during their existence in the ROI. The accuracy of the test results for vehicle detection is about 93%.