• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.12
• /
• pp.2953-2960
• /
• 2014

In the field of image recognition, circle detection is one of the most widely used techniques. Conventional algorithms are mainly based on Hough transform, which is the most straightforward algorithm for detecting circles and for providing enough robust algorithm. However, it suffers from large memory requirements and high computational loads, and sometimes tends to detect incorrect circles. This paper proposes an optimal circle detection and approximation method which is applicable for inspecting fiber optic connector endface. The proposed method finds initial center coordinates and radius based on the initial edge lines. Then, by introducing the simplified K-means algorithm, the proposed method investigates a substitute-circle by minimizing the area of non-overlapped regions. Through extensive simulations, it is shown that the proposed method can improve the error rate by as much as 67% and also can reduce the computing time by as much as 80%, compared to the Hough transform provided by the OpenCV library.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.10a
• /
• pp.83-86
• /
• 2013

In this paper, by using the Morphing, if the size of the eyes of both sides are not the same, we propose a method to correct the size of eyes area. First, by using the Haar-like feature from a input image that is input, to detect the shape of the eyes and face. After inverting the left and right eye region of one of the shape of the eyes detected sets the correspondence between the second with a line to control the shape of the eyes detected using eyes that is detected with canny edge, in the previous step. To the Warping to match the correspondence was then set in the previous step, an area of each eye. Then, I merge the image which merged in the eye area is detected from the original image. As a result, a system result of the experiment in the test image and face image seen from the front, the proposed, prove to be more efficient than a method of keying the size of the eye only.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.47 no.1
• /
• pp.7-16
• /
• 2010

Face recognition of face images is an active subject in the area of computer pattern recognition, which has a wide range of potential. Automatic extraction of face image of the feature points is an important step during automatic face recognition. Whether correctly extract the facial feature has a direct influence to the face recognition. In this paper, a new method of facial feature extraction based on Discrete Wavelet Transform is proposed. Firstly, get the face image by using PC Camera. Secondly, decompose the face image using discrete wavelet transform. Finally, we use the horizontal direction, vertical direction projection method to extract the features of human face. According to the results of the features of human face, we can achieve face recognition. The result show that this method could extract feature points of human face quickly and accurately. This system not only can detect the face feature points with great accuracy, but also more robust than the tradition method to locate facial feature image.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.47 no.5
• /
• pp.1-9
• /
• 2010

Generally, dynamic hand gesture recognition is formed through preprocessing step, hand tracking step and hand shape detection step. In this paper, we present advanced dynamic hand gesture recognizing method that improves performance in preprocessing step and hand shape detection step. In preprocessing step, we remove noise fast by using dynamic table and detect skin color exactly on complex background for controling skin color range in skin color detection method using YCbCr color space. Especially, we increase recognizing speed in hand shape detection step through detecting Start Image and Stop Image, that are elements of dynamic hand gesture recognizing, using Guideline. Guideline is edge of input hand image and hand shape for comparing. We perform various experiments with nine web-cam video clips that are separated to complex background and simple background for dynamic hand gesture recognition method in the paper. The result of experiment shows similar recognition ratio but high recognition speed, low cpu usage, low memory usage than recognition method using learning exercise.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.15 no.4
• /
• pp.159-166
• /
• 2020

The IBC (Intra-Body Communication) benefits from a wireless communication system for exchanging various kinds of digital information through wearable electronic devices and sensors. The IBC using the human body as the transmission channel allows wireless communication without the transmitting radio frequency waves to the air. This paper discusses the results of experiments on electrostatic coupling IBC based on FSK (Frequency Shift Keying) and 1 bit error correction. We implemented FSK communication and 1 bit error correction algorithm using the MCU boards and aluminum tape electrodes. The transmitter modulates digital data using 50% duty square wave as carrier signal and transmits data through human body. The receiver performs ADC (Analog to Digital Conversion) on carrier signal from human body. In order to figure out the frequency of carrier signal from ADC results, we applied zero-crossing algorithm which is used to detect the edge characteristic in computer vision. Experiment results shows that digital data modulated as square wave can be successfully transmitted through human body by applying the proposed architecture of a 1ch GPIO as a transmitter and 1ch ADC for as a receiver. Also, this paper proposes 1 bit error correction technique for reliable IBC. This technique performs error correction by utilizing the feature that carrier signal has 50% duty ratio. When 1 bit error correction technique is applied, the byte error rate at receiver side is improved around 3.5% compared to that not applied.

• Korean Journal of Optics and Photonics
• /
• v.22 no.6
• /
• pp.283-290
• /
• 2011

A Raman LIDAR system has been designed and constructed for quantitative measurement of water vapor mixing ratio. The comparison with commercial microwave radiometer and global navigation satellite system(GNSS) was performed for the precipitable water vapor(PWV) profile and total PWV. The result shows that the total GNSS-PWV and LIDAR-PWV have good correlation with each other. But, there is small difference between the two methods because of maximum measurement height in LIDAR and the GNSS method. There are some significant differences between Raman and MWR when the water vapor concentration changes quickly near the boundary layer or at the edge of a cloud. Finally we have decided that MWR cannot detect spatial changes but LIDAR can measure spatial changes.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.4 no.3
• /
• pp.133-140
• /
• 2002

Site-specific minimum temperature forecasts are critical in a short-term decision making procedure for preventive measures as well as a long-term strategy such as site selection in fruits industry. Nocturnal cold air pools frequently termed in mountainous areas under anticyclonic systems are very dangerous to the flowering buds in spring over Korea, but the spatial resolution to detect them exceeds the current weather forecast scale. To supplement the insufficient spatial resolution of official forecasts, we developed a GIS - assisted frost risk assesment scheme for using in mountainous areas. Daily minimum temperature data were obtained from 6 sites located in a 2.1 by 2.1 km area with complex topography near the southern edge of Sobaek mountains during radiative cooling nights in spring 2001. A digital elevation model with a 10 m spatial resolution was prepared for the entire study area and the cold air inflow was simulated for each grid cell by counting the number of surrounding cells coming into the processing cell. Primitive temperature surfaces were prepared for the corresponding dates by interpolating the Korea Meteorological Administration's automated observational data with the lapse rate correction. The cell temperature values corresponding to the 6 observation sites were extracted from the primitive temperature surface, and subtracted from the observed values to obtain the estimation error. The errors were regressed to the flow accumulation at the corresponding cells, delineating a statistically significant relationship. When we applied this relationship to the primitive temperature surfaces of frost nights during April 2002, there was a good agreement with the observations, showing a feasibility of site-specific frost warning system development in mountainous areas.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.12
• /
• pp.3016-3022
• /
• 2013

In this paper, we propose a novel design and implementation method to detect musical plagiarism which can provide human experts evidences to decide plagiarism using cutting-edge information technologies and thereby can solve exhaustive disputes on cases of musical plagiarism when the cases are decided by human experts' emotional preferences. We first search digital music elements to analyze music source and examine how to use these in plagiarism analysis using IT techniques. Therefore we designed music plagiarism analysis system by using MusicString which is supported in JFugue and construct AST to manipulate music plagiarism analysis efficiently.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.9
• /
• pp.1786-1792
• /
• 2007

In this paper, we proposed a recognition system for resident registration cards using ART-1 and PCA algorithm. To extract registration numbers and issue date, Sobel mask and median filter are applied first and noise removal follows. From the noise-removed image, horizontal smearing is used to extract the regions, which are binarized with recursive binarization algorithm. After that vortical smearing is applied to restore corrupted lesions, which are mainly due to the horizontal smearing. from the restored image, areas of individual codes are extracted using 4-directional edge following algorithm and face area is extracted by the morphologic characteristics of a registration card. Extracted codes are recognized using ART-1 algorithm and PCA algorithm is used to verify the face. When the proposed method was applied to 25 real registration card images, 323 characters from 325 registration numbers and 166 characters from 167 issue date numbers, were correctly recognized. The verification test with 25 forged images showed that the proposed verification algorithm is robust to detect forgery.

• Journal of IKEEE
• /
• v.25 no.3
• /
• pp.430-436
• /
• 2021

The non-contact body temperature measurement system is one of the key factors, which is manage febrile diseases in mass facilities using optical and thermal imaging cameras. Conventional systems can only be used for simple body temperature measurement in the face area, because it is used only a deep learning-based face detection algorithm. So, there is a limit to detecting abnormal symptoms of the infants and young children, who have difficulty expressing their opinions. This paper proposes an improved facial expression recognition algorithm for detecting abnormal symptoms in infants and young children. The proposed method uses an object detection model to detect infants and young children in an image, then It acquires the coordinates of the eyes, nose, and mouth, which are key elements of facial expression recognition. Finally, facial expression recognition is performed by applying a selective sharpening filter based on the obtained coordinates. According to the experimental results, the proposed algorithm improved by 2.52%, 1.12%, and 2.29%, respectively, for the three expressions of neutral, happy, and sad in the UTK dataset.