• Korean Journal of Optics and Photonics
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• v.16 no.4
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• pp.345-353
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• 2005

We proposed a new and cost-effective method fer assembling holographic pickup modules without any high resolution vision system. Assembling was accomplished by adjusting photodiode package only, leading to a low cost, holographic pickup module. Focus and tracking error signals were simply determined by comparing spot sizes and by using the 3 beam method, respectively, based on four-sectional holographic optical elements. In experiment, we assembled a hologram module and estimated performance of the proposed method fur a holographic pickup module used in compact disc system.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.2
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• pp.101-106
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• 2021

In this paper, an inspection system has been developed where pneumatic instruments are used to stretch the film using compressed air, thus the curl problem can be overcome. When the pneumatic system is applied, a line scan camera should be used instead of an area camera because the COF surface makes an arc by the air pressure. The distance between the COF and the inspection camera should be kept constant to get a clear image, thus the position of COF is to be monitored on real-time. An operating software has been also developed which is switching on/off the pneumatic system, determining the COF position using a camera vision, displaying the contour of the COF side view, sending self-diagnosis result and etc. The developed system has been examined using the actual roll of COF, which convince that the system can be an effective device to inspect the COF rolls in process.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.12
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• pp.1-7
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• 2021

The deep learning image processing technique was used to prevent accidents in lathe work caused by worker negligence. During lathe operation, when the chuck is rotated, it is very dangerous if the operator's hand is near the chuck. However, if the chuck is stopped during operation, it is not dangerous for the operator's hand to be in close proximity to the chuck for workpiece measurement, chip removal or tool change. We used YOLO (You Only Look Once), a deep learning image processing program for object detection and classification. Lathe work images such as hand, chuck rotation and chuck stop are used for learning, object detection and classification. As a result of the experiment, object detection and class classification were performed with a success probability of over 80% at a confidence score 0.5. Thus, we conclude that the artificial intelligence deep learning image processing technique can be effective in preventing incidents resulting from worker negligence in future manufacturing systems.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.83-93
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• 2013

Recently, the SURF algorithm, which is conjugated for object tracking system as part of many computer vision applications, is a well-known scale- and rotation-invariant feature detection algorithm. The SURF, due to its high computational complexity, there is essential to develop a hardware accelerator in order to be used on an IP in embedded environment. However, the SURF requires a huge local memory, causing many problems that increase the chip size and decrease the value of IP in ASIC and SoC system design. In this paper, we proposed a way to design a SURF algorithm in hardware with greatly reduced local memory by partitioning the algorithms into several Sub-IPs using external memory and a DMA. To justify validity of the proposed method, we developed an example of simplified object tracking algorithm. The execution speed of the hardware IP was about 31 frame/sec, the logic size was about 74Kgate in the 30nm technology with 81Kbytes local memory in the embedded system platform consisting of ARM Cortex-M0 processor, AMBA bus(AHB-lite and APB), DMA and a SDRAM controller. Hence, it can be used to the hardware IP of SoC Chip. If the image processing algorithm akin to SURF is applied to the method proposed in this paper, it is expected that it can implement an efficient hardware design for target application.

• The KIPS Transactions:PartA
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• v.14A no.5
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• pp.301-308
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• 2007

This paper proposes high performance coprocessor architecture for real time dense disparity computation based on a phase-based binocular stereo matching technique called local weighted phase-correlation(LWPC). The algorithm combines the robustness of wavelet based phase difference methods and the basic control strategy of phase correlation methods, which consists of 4 stages. For parallel and efficient hardware implementation, the proposed architecture employs SIMD(Single Instruction Multiple Data Stream) architecture for each functional stage and all stages work on pipelined mode. Such that the newly devised pipelined linear array processor is optimized for the case of row-column image processing eliminating the need for transposed memory while preserving generality and high throughput. The proposed architecture is implemented with Xilinx HDL tool and the required hardware resources are calculated in terms of look up tables, flip flops, slices, and the amount of memory. The result shows the possibility that the proposed architecture can be integrated into one chip while maintaining the processing speed at video rate.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.220-223
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• 2004

Automatic image registration is an essential element of remote sensing because remote sensing system generates enormous amount of data, which are multiple observations of the same features at different times and by different sensor. The general process of automatic image registration includes three steps: 1) The extraction of features to be used in the matching process, 2) the feature matching strategy and accurate matching process, 3) the resampling of the data based on the correspondence computed from matched feature. For step 2) and 3), we have developed an algorithms for automated registration of satellite images with RANSAC(Random Sample Consensus) in success. However, for step 1), There still remains human operation to generate GCP Chips, which is time consuming, laborious and expensive process. The main idea of this research is that we are able to automatically generate GCP chips with comer detection algorithms without GPS survey and human interventions if we have systematic corrected satellite image within adaptable positional accuracy. In this research, we use SUSAN(Smallest Univalue Segment Assimilating Nucleus) algorithm in order to detect the comer. SUSAN algorithm is known as the best robust algorithms for comer detection in the field of compute vision. However, there are so many comers in high-resolution images so that we need to reduce the comer points from SUSAN algorithms to overcome redundancy. In experiment, we automatically generate GCP chips from IKONOS images with geo level using SUSAN algorithms. Then we extract reference coordinate from IKONOS images and DEM data and filter the comer points using texture analysis. At last, we apply automatically collected GCP chips by proposed method and the GCP by operator to in-house automatic precision correction algorithms. The compared result will be presented to show the GCP quality.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.87-93
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• 2012

In this paper, we proposed a faulty pattern detection algorithm of TCP(Tape Carrier Package)/COF(Chip On Film), and implemented a real-time system for inspecting TCP/COF. Since TCP/COF has very high resolution having several micro meters, the human operator should visually inspect all the parts through microscope. In this work, we implement an inspection system to detect the faulty pattern, so the operator can visually inspect only the designated parts by the inspection system through the monitor. The proposed defects detection algorithm for TCP/COF packages is implemented by the pattern matching method based on subtracting the reference image from test image. To evaluate performance of the proposal system. we made various experiments according to type of CCD camera and light source as well as illumination projection method. From experimental results, it is confirmed that the proposed system makes it possible to detect effectively the defective TCP/COF film.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.165-171
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• 2004

Owing to small sizes and high density to the semiconductor It, it is difficult to discriminate the defects of ICs by human eyes. High precision inspection system with computer vision is essentially established for the manufacturing process due to the variety of defective parts. Especially it is difficult to implement the algorithm for the coplanarity of IC leads. Therefore in this paper, the inspection system which can detect the defects of the SOP types of ICs having 1cm${\times}$0.5cm of the chip size is implemented and evaluated it's performance. In order to optimally detect various items, some principles of geometry are theoretically presented , length measurement, pitch measurement, angle measurement, brightness of image and correcton of position. The interface circuit is designed for implementation of inspection system and connected the HANDLER. In the result, the system could detect two ICs' defects per second and confirmed the resolution of 20$\mu$m per pixel.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.7
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• pp.56-62
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• 2019

The high-precision laser scriber carries out scribing alumina ceramic substrates for manufacturing ultra-small chip resistors. The ceramic substrates are loaded, aligned, scribed, transferred, and unloaded. The entire process is fully automated, thereby minimizing the scribing cycle time of the ceramic substrates and improving the throughput. The scriber consists of the laser optical system, pick-up module of ceramic substrates, pre-alignment module, TH axis drive work table, automation module for substrate loading / unloading, and high-speed scribing control S/W. The loader / unloader unit, which has the greatest influence on the scribing cycle time of the substrates, carries the substrates to the work table that carries out the cutting line work by driving the X and Y axes as well as by adsorbing the ceramic substrates. The loader / unloader unit consists of the magazine up / down part, X-axis drive part for conveying the substrates to the left and right direction, and the vision part for detecting the edge of the substrate for the primary pre-alignment of the substrates. In this paper, the laser scribing machining simulation is performed by applying the instrument mechanism of each component module. Through this study, the scribing machining process is first verified by analyzing the process operation and work area of each module in advance. In addition, the scribing machining process is optimized by comparing and analyzing the scribing cycle time of one ceramic substrate according to the alignment stage module speed.

• Journal of Korean Neurosurgical Society
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• v.29 no.1
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• pp.58-65
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• 2000

Objective : Thoracolumbar junction is second most common level of injury next to cervical spine. The object of this study is to study the usefulness of surgical titanium mesh instead of bone graft, as well as to evaluate the correction of spinal deformity and safety of early ambulation in patients with injury at thoracolumbar junction. Patients and Methods : This review included 51 patients who were operated from July 1994 to December 1997. The injured spine is considered to be unstable, if it shows involvement of two or more columns, translatory displacement more than 3.5mm, decrease more than 35% in height of vertebral body and progression of malalignment in serial X-ray. The decision to operate was determined by (1) compression of spinal cord or cauda eguina, (2) unstable fracture, (3) malalignment and (4) fracture dislocation. The procedure consisted of anterior decompression through corpectomy and internal fixation with anterior instrument and surgical titanium mesh which was impacted with gathered bone chip from corpectomy. Results : Fifty-one patients were followed up for at least 12 months. The main causes of injury were fall and vehicle accident. The twelfth thoracic and the first and the second lumbar vertebrae were frequently involved. Complete neural decompression was possible under direct vision in all cases. Kyphotic angulation occurred in a patient. Radiologic evaluation showed correction of deformity and no distortion or loosening of surgical titanium mesh with satisfactory fixation postoperatively. Conclusions : We could obtain neurological improvement, relief of pain, immediate stabilization and early return to normal activities postoperatively. Based on these results, authors recommend anterior decompression and internal fixation with surgical titanium mesh in thoracolumbar unstable spine injuries.