• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.5
• /
• pp.211-220
• /
• 2022

Recently, research on smart factories triggered by the 4th industrial revolution is being actively conducted. Accordingly, the manufacturing industry is conducting various studies to improve productivity and quality based on deep learning technology with robust performance. This paper is a study on the method of detecting tire surface defects in the visual inspection stage of the tire manufacturing process, and introduces a tire surface defect detection method using a depth image acquired through a 3D camera. The tire surface depth image dealt with in this study has the problem of low contrast caused by the shallow depth of the tire surface and the difference in the reference depth value due to the data acquisition environment. And due to the nature of the manufacturing industry, algorithms with performance that can be processed in real time along with detection performance is required. Therefore, in this paper, we studied a method to normalize the depth image through relatively simple methods so that the tire surface defect detection algorithm does not consist of a complex algorithm pipeline. and conducted a comparative experiment between the general normalization method and the normalization method suggested in this paper using YOLO V3, which could satisfy both detection performance and speed. As a result of the experiment, it is confirmed that the normalization method proposed in this paper improved performance by about 7% based on mAP 0.5, and the method proposed in this paper is effective.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.10 no.5
• /
• pp.359-363
• /
• 2017

The LED (Liquid Emitting Diode) frame device is a big part of the representative display industry in Korea. LED is an essential part for TV, monitor, notebook, and mobile phone. In Japan, Taiwan, China and other countries, investment in LEDs has been strengthened, and productivity has become an important issue. However, as the size of the parts becomes smaller, the inconsistent inspection by the human eye becomes a problem of reliability, so that the automatic inspection process becomes an essential issue in the field of LED module inspection. In this paper, we investigate defects in visual inspection process using computer vision technology. The inspection of the LED frame is made quickly and accurately, thereby improving the efficiency of the process and shortening the inspection time. As a result of applying the inspection system to the field, we confirmed that it is possible to inspect quickly and accurately.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.2
• /
• pp.160-166
• /
• 2020

As mobile-based hardware technology develops, many kinds of applications are also being developed. In addition, there is an increasing demand to automatically check that the interface of these applications works correctly. In this paper, we describe a method for accurately detecting faulty images from applications by comparing major characteristics from input color images. For this purpose, our method first extracts major characteristics of the input image, then calculates the differences in the extracted major features, and decides if the test image is a normal image or a faulty image dissimilar to the reference image. Experiment results show that the suggested approach robustly determines similar and dissimilar images by comparing major characteristics from input color images. The suggested method is expected to be useful in many real application areas related to computer vision, like video indexing, object detection and tracking, image surveillance, and so on.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.11
• /
• pp.6922-6931
• /
• 2014

The development of modern science and technology and computer engineering breakthroughs in the field of information and communication have brought about many changes in lifestyle. The government announced the goal of educational policy in 2030 to educate people in future society on a future-oriented perspective. Changes in the curriculum along with changes in educational facilities are essential. Therefore, the operation of a classroom should be associated with classroom spatial information. The BIM design based on 3D geometry information was designed. The BIM design can link the design information and non-geometric information of spatial information. This study examined the operation of school facilities based on classroom spatial information with BIM. This study suggests standardization of classroom spatial information based on BIM. The scenarios of BIM ordering and design for departmentalized classrooms management is proposed.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.48 no.6
• /
• pp.114-122
• /
• 2011

We propose an automatic localization technique based on Uniform Arc Length Sampling (UALS) of 360 degree range sensor data. The proposed method samples 3D points from dense a point-cloud which is acquired by the sensor, registers the sampled points to a digital surface model(DSM) in real-time, and determines the location of an Unmanned Ground Vehicle(UGV). To reduce the sampling and registration time of a sequence of dense range data, 3D range points are sampled uniformly in terms of ground sample distance. Using the proposed method, we can reduce the number of 3D points while maintaining their uniformity over range data. We compare the registration speed and accuracy of the proposed method with a conventional sample method. Through several experiments by changing the number of sampling points, we analyze the speed and accuracy of the proposed method.

• Spatial Information Research
• /
• v.19 no.1
• /
• pp.29-40
• /
• 2011

GOCI the world first Ocean Color Imager in Geostationary Orbit, which could obtain total 8 images of the same region a day, however, its spatial resolution(500m) is not enough to use for the accurate land application, Super Resolution(SR), reconstructing the high resolution(HR) image from multiple low resolution(LR) images introduced by computer vision field. could be applied to the time-series remotely sensed images such as GOCI data, and the higher resolution image could be reconstructed from multiple images by the SR, and also the cloud masked area of images could be recovered. As the precedent study for developing the efficient SR method for GOCI images, on this research, it reproduced the simulated data under the acquisition process of the remote sensed data, and then the simulated images arc applied to the proposed algorithm. From the proposed algorithm result of the simulated data, it turned out that low resolution(LR) images could be registered in sub-pixel accuracy, and the reconstructed HR image including RMSE, PSNR, SSIM Index value compared with original HR image were 0.5763, 52.9183 db, 0.9486, could be obtained.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.47 no.2
• /
• pp.68-76
• /
• 2010

Touch-enabled technology is increasingly being accepted as a main communication interface between human and computers. However, conventional touchscreen technologies, such as resistive overlay, capacitive overlay, and SAW(Surface Acoustic Wave), are not cost-effective for large screens. As an alternative to the conventional methods, we introduce a newly emerging method, an optical imaging touchscreen which is much simpler and more cost-effective. Despite its attractive benefits, optical imaging touchscreen has to overcome some problems, such as heavy computational complexity, intermittent ghost points, and over-sensitivity, to be commercially used. Therefore, we designed a hardware controller for signal processing and multi-coordinate computation, and proposed Infrared-blocked DA(Dark Area) manipulation as a solution. While the entire optical touch control took 34ms with a 32-bit microprocessor, the designed hardware controller can manage 2 valid coordinates at 200fps and also reduce energy consumption of infrared diodes from 1.8Wh to 0.0072Wh.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.9
• /
• pp.2129-2137
• /
• 2015

Lots of research and development works have been actively focused on the self-driving vehicles, locally and globally. In order to implement the self-driving vehicles, lots of fundamental core technologies need to be successfully developed and, specially, it is noted that traffic lights detection and recognition system is an essential part of the computer vision technologies in the self-driving vehicles. Up to nowadays, most conventional algorithm for detecting and recognizing traffic lights are mainly based on the color signal analysis, but these approaches have limits on the performance improvements that can be achieved due to the color signal noises and environmental situations. In order to overcome the performance limits, this paper introduces the morphological analysis for the traffic lights recognition. That is, by considering the color component analysis and the shape analysis such as rectangles and circles simultaneously, the efficiency of the traffic lights recognitions can be greatly increased. Through several simulations, it is shown that the proposed method can highly improve the recognition rate as well as the mis-recognition rate.

• Journal of Broadcast Engineering
• /
• v.23 no.2
• /
• pp.261-273
• /
• 2018

As progress on image processing, computer vision and display technologies aroused market's interests on generation and consumption of various types of media, interests on UWV media are also increasing. In context of consumption of UWV media, to effectively manage load of servers and resources of end terminal devices and provide user-derived services, technology which enables users to select and consume interested regions of media seems to be needed. Here, this paper proposes a method for description and transmission of spatial relationships among media, which composes UWV, by expanding MPEG-CI and Layout signaling to enable users' selective consumption of UWV media.

• The Journal of Korean Institute of Next Generation Computing
• /
• v.15 no.5
• /
• pp.31-42
• /
• 2019

With the recent development of deep learning technology, remarkable achievements have been made in many research areas of computer vision. Deep learning has also made dramatic improvement in two-dimensional or three-dimensional human pose estimation based on a single image, and many researchers have been expanding the scope of this problem. The human pose estimation is one of the most important research fields because there are various applications, especially it is a key factor in understanding the behavior, state, and intention of people in image or video analysis. Based on this background, this paper surveys research trends in estimating human poses based on a single image. Because there are various research results for robust and accurate human pose estimation, this paper introduces them in two separated subsections: 2D human pose estimation and 3D human pose estimation. Moreover, this paper summarizes famous data sets used in this field and introduces various studies which utilize human poses to solve their own problem.