• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.107-114
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• 2016

Recently, 3D related technology has become a hot topic for IT. 3D technologies such as 3DTV, Kinect and 3D printers are becoming more and more popular. According to the flow of the times, the goal of this study is that the general public is exposed to 3D technology easily. we have developed a web-based application program that enables 3D modeling of facial front and side photographs using a mobile phone. In order to realize 3D modeling, two photographs (front and side) are photographed with a mobile camera, and ASM (Active Shape Model) and skin binarization technique are used to extract facial height such as nose from facial and side photographs. Three-dimensional coordinates are generated using the face extracted from the front photograph and the face height obtained from the side photograph. Using the 3-D coordinates generated for the standard face model modeled with the standard face as a control point, the face becomes the face of the subject when the RBF (Radial Basis Function) interpolation method is used. Also, in order to cover the face with the modified face model, the control point found in the front photograph is mapped to the texture map coordinate to generate the texture image. Finally, the deformed face model is covered with a texture image, and the 3D modeled image is displayed to the user.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.834-841
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• 1996

Egg production in Korea is becoming automated with a large scale farm. Although many operations in egg production have been and cracks are regraded as a critical problem. A computer vision system was built to generate images of a single , stationary egg. This system includes a CCD camera, a frame grabber board, a personal computer (IBM PC AT 486) and an incandescent back lighting system. Image processing algorithms were developed to inspect egg shell and to sort eggs. Those values of both gray level and area of dark spots in the egg image were used as criteria to detect holes in egg and those values of both area and roundness of dark spots in the egg and those values of both area and roundness of dark spots in the egg image were used to detect cracks in egg. Fro a sample of 300 eggs. this system was able to correctly analyze an egg for the presence of a defect 97.5% of the time. The weights of eggs were found to be linear to both the projected area and the perimeter of eggs v ewed from above. Those two values were used as criteria to sort eggs. Accuracy in grading was found to be 96.7% as compared with results from weight by electronic scale.

• Journal of Korean Society of Transportation
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• v.14 no.4
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• pp.107-129
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• 1996

Recently, surveillance system designed to collect various trsffic information are becoming new areas of development . Among these, the image detector is a ayatem which can measure the travel time and speed in realtime and this is emerging as the most effcient tool to be available in future related areas. But in measuring wide-area information in realtime, the image detector are yet full of problem in its accuracy. The aim of this ahesis is to develop an algorithms which can collect wide-area information such as travel time and travel speed in urban networks and freeways in realtime. The information on wide-area such as travel time and travel speed is important in accomplishing strategic function in traffic control. The algorithm developed from this study is based on the image tracking model which tracks a moving vehicle form image datas collected continuously, and is constructed to perform realtime measurement. To evaluate the performance of the developed algorithms, 600 ind vidual vehicles in total were used as data for the study, and this evaluation was carried out with the differenciation of day and night condition at the access roads in front of AJou University, In the statistical analysis results, the error rate was recorded as 5.69% and it has proved to be applicable on the field in both day and noght conditions.

• Laser Solutions
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• v.12 no.1
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• pp.19-24
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• 2009

Because of its fast and precise welding performance, laser welding is becoming a new excellent welding method. However, the precise focusing and robust seam tracking are required to apply laser welding to the practical fields. In order to laser weld a type of T joint like a circular pipe on a square pipe, which could be met in the three dimensional structure such as an aluminum space frame, a visual sensor system was developed for automation of focusing and seam tracking. The developed sensor system consists of a digital CCD camera, a structured laser, and a vision processor. It is moved and positioned by a 2-axis motorized stage, which is attached to a 6 axis robot manipulator with a laser welding head. After stripe-type structured laser illuminates a target surface, images are captured through the digital CCD camera. From the image, seam error and defocusing error are calculated using image processing algorithms which includes efficient techniques handling continuously changed image patterns. These errors are corrected by the stage off-line during welding or teaching. Laser welding of a circular pipe on a square pipe was successful with the vision tracking system by reducing the path positioning and de focusing errors due to the robot teaching or a geometrical variation of specimens and jig holding.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.252-255
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• 2014

Image treatment is becoming mainstream as the demand for image restoration has drastically increased in the digital era. But in the process of acquiring, transmitting and treating video data, the salt and pepper noise damages the image. One of the major methods used for restoring images are SMF(standard median filter), CWMF(center weighted median filter) and SWMF(switching weighted median filter), but these filters all leave a bit to be desired in terms of removing noise and preserving edge. Therefore, a transformed median filter is suggested through the algorithm presented for the restoration of damaged images.

• Journal of Broadcast Engineering
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• v.26 no.1
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• pp.88-98
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• 2021

Recently, the crime prevention and culprit identification even in a low illuminated environment by CCTV is becoming ever more important. In a low lighting situation, CCTV applications capture images under infrared lighting since it is unobtrusive to human eye. Although the infrared lighting leads to advantage of capturing an image with abundant fine texture information, it is hard to capture the color information which is very essential in identifying certain objects or persons in CCTV images. In this paper, we propose a method to acquire color information through DCGAN from an image captured by CCTV in a low lighting environment with infrared lighting and a method to remove color noise in the acquired color image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4426-4442
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• 2020

Since scene segmentation is becoming a hot topic in the field of autonomous driving and medical image analysis, researchers are actively trying new methods to improve segmentation accuracy. At present, the main issues in image semantic segmentation are intra-class inconsistency and inter-class indistinction. From our analysis, the lack of global information as well as macroscopic discrimination on the object are the two main reasons. In this paper, we propose a Densely connected residual Attention network (DA-Res2Net) which consists of a dense residual network and channel attention guidance module to deal with these problems and improve the accuracy of image segmentation. Specifically, in order to make the extracted features equipped with stronger multi-scale characteristics, a densely connected residual network is proposed as a feature extractor. Furthermore, to improve the representativeness of each channel feature, we design a Channel-Attention-Guide module to make the model focusing on the high-level semantic features and low-level location features simultaneously. Experimental results show that the method achieves significant performance on various datasets. Compared to other state-of-the-art methods, the proposed method reaches the mean IOU accuracy of 83.2% on PASCAL VOC 2012 and 79.7% on Cityscapes dataset, respectively.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.53-64
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• 2023

Early detection of endometrial carcinoma in uterus is essential for effective treatment. Endometrial carcinoma is the worst kind of endometrium cancer among the others since it is considerably more likely to affect the additional parts of the body if not detected and treated early. Non-invasive medical computer vision, also known as medical image processing, is becoming increasingly essential in the clinical diagnosis of various diseases. Such techniques provide a tool for automatic image processing, allowing for an accurate and timely assessment of the lesion. One of the most difficult aspects of developing an effective automatic categorization system is the absence of huge datasets. Using image processing and deep learning, this article presented an artificial endometrium cancer diagnosis system. The processes in this study include gathering a dermoscopy images from the database, preprocessing, segmentation using hybrid Fuzzy C-Means (FCM) and optimizing the weights using the Whale Optimization Algorithm (WOA). The characteristics of the damaged endometrium cells are retrieved using the feature extraction approach after the Magnetic Resonance pictures have been segmented. The collected characteristics are classified using a deep learning-based methodology called Long Short-Term Memory (LSTM) and Bi-directional LSTM classifiers. After using the publicly accessible data set, suggested classifiers obtain an accuracy of 97% and segmentation accuracy of 93%.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.813-821
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• 2022

Intelligent monitoring, life entertainment, medical rehabilitation, and other fields are only a few examples where visual image technology is becoming increasingly sophisticated and playing a significant role. Recognizing Wushu, or martial arts, movements through the use of visual image technology helps promote and develop Wushu. In order to segment and extract the signals of Wushu movements, this study analyzes the denoising of the original data using the wavelet transform and provides a sliding window data segmentation technique. Wushu movement The Wushu movement recognition model is built based on the hidden Markov model (HMM). The HMM model is trained and taught with the help of the Baum-Welch algorithm, which is then enhanced using the frequency weighted training approach and the mean training method. To identify the dynamic Wushu movement, the Viterbi algorithm is used to determine the probability of the optimal state sequence for each Wushu movement model. In light of the foregoing, an HMM-based martial arts movements recognition model is developed. The recognition accuracy of the HMM model increases to 99.60% when the number of samples is 4,000, which is greater than the accuracy of the SVM (by 0.94%), the CNN (by 1.12%), and the BP (by 1.14%). From what has been discussed, it appears that the suggested system for detecting martial arts acts is trustworthy and effective, and that it may contribute to the growth of martial arts.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.3
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• pp.91-101
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• 2011

Internet is becoming increasingly popular due to the rapid development of information and communication technology. There has been a convenient social activities such as the mutual exchange of information, e-commerce, internet banking, etc. through cyberspace on a computer. However, by using the convenience of the internet, the personal IDs(identity card, driving license, passport, student ID, etc.) represented by the electronic media are exposed on the internet frequently. Therefore, this study propose a feature extraction method to analyze the characteristics of image files containing personal information and a image retrieval method to find the images using the extracted features. The proposed method selects the feature information from color, texture, and shape of the images, and the images as searched by similarity analysis between feature information. The result which it experiments from the image which it acquires from the web-based image DB and correct image retrieval rate is 89%, the computing time per frame is 0.17 seconds. The proposed method can be efficiently apply a system to search the image files containing personal information and to determine the criteria of exposure of personal information.