• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.3
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• pp.472-478
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• 2012

The inspection machine in PCB (printed circuit board) assembly line checks assembly errors by inspecting the images inside of the component inspection region. The component inspection region consists of region of component package and region of soldering. It is necessary to extract the regions automatically for auto-teaching system of the inspection machine. We propose an image segmentation method to extract the component inspection regions automatically from images of PCB. The acquired image is transformed to HSI color model, and then segmented by several regions by clustering method. We develop a modified K-means algorithm to increase the accuracy of extraction. The heuristics generating the initial clusters and merging the final clusters are newly proposed. The vertical and horizontal projection is also developed to distinguish the region of component package and region of soldering. The experimental results are presented to verify the usefulness of the proposed method.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.291-294
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• 2003

In this paper, 2D and 3D inspection algorithm for printed solder on PCB is introduced. The aim of inspection is the detection of error such as rich solder poor solder and missing solder. For Inspection, laser distance sensor is used. For 2D inspection, laser image that is created by normalizing laser data between 0 and 255 are used. Reference Image is made using gerber file. Image processing algorithm is used for 2D inspection. By adding thickness of metal stencil to laser image, volume for solder can be calculated and 3D inspection is carried out.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.1
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• pp.66-72
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• 2004

To assess tunnel safety, cracks in tunnel lining are measured by inspectors, who observe cracks with their naked eyes and record them. But manual inspection is slow, and measured crack data is subjective. Therefore, this study proposes inspection system fur measuring cracks in tunnel lining and providing objective crack data to be used in safety assessment. The system consists of On-vehicle system and Laboratory system. On-Vehicle system acquires image data with line CCD camera on scanning along the tunnel lining. Laboratory system extracts crack information from the acquired image using image processing. Measured crack information is crack thickness, length and orientation. To improve accuracy of crack recognition, the geometric properties and patterns of cracks in concrete structure were applied to image processing. The proposed system was verified with experiments in both laboratory environment and field environment such as subway tunnel.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.5
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• pp.259-265
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• 2024

In this paper, we propose an automatic display defect detection system using image processing. The existing inspection by operators has the disadvantage that human errors may occur due to the operator's skill level, fatigue, etc., and that standardization and quantification are difficult. It also has disadvantages such as the limited inspection speed and the cost of the operator's education. The proposed system automatically detects various display defects through image processing algorithms. It was developed based on the Jetson Nano, one of the most popular SBCs (Single Board Computers), and it has a conveyor belt to automatically moves the display to the inspection position. By providing a human machine interface (HMI), the operator can check the inspection information in real time, and control the inspection flow. By storing the inspection results as a log file, the operator can check the inspection results at any time, such as the time taken to perform each algorithm and the location of the detected defects. In addition, a multi-threaded structure was adopted. The camera's operations and inspection algorithms are executed in parallel in different threads, which can shorten the inspection time compared to the system based on a single-threaded structure. The experimental results prove the defect detection capability of the system and the efficiency of the inspection time.

• Journal of Korea Multimedia Society
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• v.14 no.3
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• pp.356-367
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• 2011

In this paper, we proposed a new car engine sealing inspection system based on image processing and understanding. The car engine sealing inspection plays very important role for protecting leakage caused by inappropriate sealing, which is a crucial point for productivity of car engines. The proposed inspection system has been aimed to enhance the previously proposed sealing inspection systems based on image processing, which have high computation complexity and low performance for correctly inspecting some contamination by oil with similar color with that of sealing. Moreover, the previously proposed system has a difficulty in installing the camera system on the sealing machine. The proposed system considers a difference of images before and after sealing obtained from one static camera. By utilizing a difference of images, the proposed system shows very robust performance using a proposed simple depth checking algorithm for some contamination cases by oil with similar color with that of sealing and the total inspection system is simple and cheap to implement. According to the experiments conducted in a real car product line, the proposed inspection system shows better inspection performance and needs smaller implementation cost than three other previously proposed system working in current car sealing inspection systems.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.05a
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• pp.479-485
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• 2004

The purpose of this study is to develop a practical image inspection system that could recognize it correctly, endowing flexibility to the productive field, although the same object for work will be changed in the size and rotated. In this experiment, it selected a fighter, rotating the direction from $30^{\circ}\;to\;45^{\circ}$ simultaneously while changing the size from 1/4 to 1/16, as an object inspection without using another hardware for exclusive image processing. The invariant moments, Hu has suggested, was used as feature vector moment descriptor. As a result of the experiment the image inspection system developed from this research was operated in real-time regardless of the chance of size and rotation for the object inspection, and it maintained the correspondent rates steadily above from 94% to 96%. Accordingly, it is considered as the flexibility can be considerably endowed to the factory automation when the image inspection system developed from this research is applied to the productive field.

• Journal of Korea Multimedia Society
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• v.12 no.3
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• pp.397-408
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• 2009

Image training is a very important yet difficult state for automated visual inspection using computers. Because the size of parts for the recently produced PCB (Printed Circuit Board) becomes smaller and circuit patterns gradually become more complex, a difficult and complex training process is becoming a big problem within an industry where development cycle for new products is short and various products must be inspected. This research produced a reference image by using CAD (Gerber) file which becomes a standard for PCB automatic visual inspection. Reference image from a Gerber file guarantees PCB patterns with no defects. Through system implementation and experimentation, Gerber file is used in order to propose a plan which allows an easy training process for PCB automatic visual inspection system.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.24-29
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• 1996

The seniconductor, which is precision product, requires many inspection processes. The surface conditions of the semiconductor chip effect on the functions of the semiconductors. The defects of the chip surface is crack or void. Because general inspection method requires many inspection processes, the inspection system which searches immediately and preciselythe defects of the semiconductor chip surface. We propose the inspection method by using the computer vision system. This study presents an image processing algorithm for inspecting the surface defects(crack, void)of the semiconductor test samples. The proposed image processing algorithm aims to reduce inspection time, and to analyze those experienced operator. This paper regards the chip surface as random texture, and deals with the image modeling of randon texture image for searching the surface defects. For texture modeling, we consider the relation of a pixel and neighborhood pixels as noncasul model and extract the statistical characteristics from the radom texture field by using the 2D AR model(Aut oregressive). This paper regards on image as the output of linear system, and considers the fidelity or intelligibility criteria for measuring the quality of an image or the performance of the processing techinque. This study utilizes the variance of prediction error which is computed by substituting the gary level of pixel of another texture field into the two dimensional AR(autoregressive model)model fitted to the texture field, estimate the parameter us-ing the PAA(parameter adaptation algorithm) and design the defect detection filter. Later, we next try to study the defect detection search algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.185-192
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• 2021

Various methods have been proposed to determine the defect detection of welding bead, and recently sensor data and image data inspection have been steadily announced. There are advantages that sensor data inspection is highly accurate, and two-dimensional-based image data inspection is able to determine the position of the welding bead. However, when analyzing only with sensor data, it is difficult to determine whether the welding has been performed at the correct position. On the other hand, the image data inspection does not have high accuracy due to noise and measurement errors. In this paper, we propose a method that can complement the shortcomings of each inspection method and increase its advantages to improve accuracy and speed up inspection by fusing sensor data inspection which are average current, average volt, and mixed gas data, and image data inspection methods and is implemented as software. In addition, it is intended to allow users to conveniently and intuitively analyze and grasp the results by performing analysis using a graphical user interface(GUI) and checking the data and inspection results used for the inspection. Sensor inspection is performed using the characteristics of each sensor data, and image data is inspected by applying a morphology geodesic active contour algorithm. The experimental results showed 98% accuracy, and when performing the inspection on the four image data, and sensor data the inspection time was about 1.9 seconds, indicating the performance of software that can be used as a real-time inspector in the welding process.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.2
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• pp.25-31
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• 2009

The image processing methods are widely used in many industrial fields to detect defections in inspection devices. In this study an image processing method was conducted for the detection of abnormal pixels in a OLED(Organic Light Emitting Diode) type panel which is used for small size displays. The display quality of an OLED device is dependent on the pixel formation quality. So, among the so many pixels, to find out the faulty pixels is very important task in manufacturing processing or inspection division. We used a line scanning type BW(Black & White) camera which has very high resolution characteristics to acquire an image of display pixel patterns. And the various faulty cases in pixel abnormal patterns are considered to detect abnormal pixels. From the results of the research, the normal BW pixel image could be restored to its original color pixel.