• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1079-1082
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• 2005

This paper deals with the algorithm development that inspects defects such as Lens Focus, Focus check, Black Defect, Dark Defect, Dim Defect, Color Defect, and Line Defect, Angle Defect, IrisAgc Defect caused by the process of 2M Class Compact Camera Module (CCM). Domestic market was majorly comprised of VGA(0.3 million pixel) market. But in the middle of year 2004, camera phone with Mega Pixel has appeared, and it is estimated that the camera phone with Mega Pixel will take up to 28% of total phone sales if it is released in the end of year 2004. Since the inspection of finished products is done manually, it is major obstacle in production increment In this paper, to solve these problems, we developed the imaging processing algorithm to inspect the defects in captured image of assembled CCM. The performances of the developed inspection system and we can recognize various types of defect of CCM modules with good accuracy and high speed

• Transactions of Materials Processing
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• v.10 no.2
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• pp.151-159
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• 2001

Flow defect of a piston-pin for automobile parts is investigated in this study. In combined cold extrusion of piston-pin, lapping defect, which is a kind of flow defect, appears by the dead metal zone. This appearance evidently happens in products with a thin thickness to be pierced for the dimensional accuracy and the decrease of material loss. The flow defect that occurs in piston-pin has bad effects on the strength and the fatigue life of piston-pin. Therefore, it is important to predict and prevent defects in the early stage of process design. The best method that can prevent flow defect is removing or reducing dead metal zone through material flow control. The finite element simulations are applied to analyze the flow defect. This study proposes processes for preventing flow defect by removing dead metal zone. Then the results are compared with the experimental ones for verification. These FE simulation results are in good agreement with the experimental ones.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.3
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• pp.256-261
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• 2013

In the steel manufacturing area, researches for defect inspection receive a big attention for quality control. This paper proposes an algorithm to detect a scratch defect on steel billets. This algorithm takes ROIs (Regions of Interest), and extracts 11 features which represent properties of defect on a ROI. SVM (Support Vector Machine) is used to classify defect and normal ROIs. The algorithm classifies a frame image of a Billet as a defect image if there is one or more defect ROIs. In the experiments, the proposed algorithm had reliable classifying accuracy.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.946-949
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• 2005

This paper deals with the algorithm development that inspects defects such as Bright Defect Dots, Dark Defect Dots, and Line Defect caused by the process of LCD(Liquid Crystal Display). While most of LCD production process is automated, the inspection of LCD panel and its appearance depends on manual process. So, the quality of the inspection is affected by the condition of worker. Especially, the more LCD size increases, the more the worker feels fatigued, which causes the probability of miss judgement. So, the automated inspection is required to manage the consistent quality of the product and reduce the production costs. In this paper, to solve these problems, we developed the imaging processing algorithm to inspect the defects in captured image of LCD. Experimental results reveal that we can recognize various types of defect of LCD with good accuracy and high speed.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.4
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• pp.247-252
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• 2016

In this paper, we propose a new defect detection technology for micro-defect on the surface of steel products. Due to depth and size of microscopic defect, slop of surface and vibration of strip, the conventional optical method cannot guarantee the detection performance. To solve the above-mentioned problems and increase signal to noise ratio, a novel retro-schlieren method that consists of retro reflector and knife edge is proposed. Moreover dual switching lighting method is also applied to distinguish uneven micro defects and surface noise. In proposed method, defective regions are represented by a black and white pattern. This pattern is detected by a defect detection algorithm with Gabor filter. Experimental results by simulator for sample defects of cold rolled steel show that the proposed method is effective.

• Journal of information and communication convergence engineering
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• v.10 no.3
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• pp.295-299
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• 2012

Defect generation during organic bottom anti-reflective coating (BARC) in the photo lithography process is closely related to humidity control in the BARC coating unit. Defects are related to the water component due to the humidity and act as a blocking material for the etching process, resulting in an extreme pattern bridging in the subsequent BARC etching process of the poly etch step. In this paper, the lower limit for the humidity that should be stringently controlled for to prevent defect generation during BARC coating is proposed. Various images of defects are inspected using various inspection tools utilizing optical and electron beams. The mechanism for defect generation only in the specific BARC coating step is analyzed and explained. The BARC defect-induced gate pattern bridging mechanism in the lithography process is also well explained in this paper.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1509-1511
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• 2015

Defect detection is one of the most challenging problems in industrial quality control. In this study we developed a vision-based defect detection system for wafer production. To achieve high-accuracy detection, Otsu method was improved so that it can handle both unimodal and bimodal distributions. After thresholding, detected defect regions in the wafer are classified and grouped into user-defined defect categories. The experimental result has proved the efficiency of our system.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.974-978
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• 2013

AVI (Automatic Vision Inspection) systems automatically detect defect features and measure their sizes via camera vision. AVI systems usually report different measurements on the same defect with some variations on position or rotation mainly because different images are provided. This is caused by possible variations from the image acquisition process including optical factors, nonuniform illumination, random noises, and so on. For this reason, conventional area based defect measuring methods have problems of robustness and consistency. In this paper, we propose a new defect size measuring method to overcome this problem, utilizing volume information that is completely ignored in the area based defect measuring method. The results show that our proposed method dramatically improves the robustness and consistency of defect size measurement.

• Imaging Science in Dentistry
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• v.34 no.1
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• pp.35-48
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• 2004

Purpose: To investigate the effect of rhBMP-2 on the healing of bone defect in the low calcium diet rat. Materials and Methods: To prepare the experimental model, control group was fed a normal diet and experimental group was fed a low calcium diet for 3 weeks. And then, 4 mm bicortical perforated bone defect was made on mandibular body of each rats. Experimental group was subdivided into two groups; experimental group 1 (rats given a low calcium diet before and after bone defect) and experimental group 2 (rats given a low calcium diet before and after bone defect with rhBMP-2 application). At 1, 3, 5 and 7 weeks after bone defect formation, the rats were terminated. The healing of bone defect was assessed by three-dimensional computerized tomography, soft x-ray radiography, and histopathological examination. Results : The wound healing of the bone defect for control group, experimental group 1, and experimental group 2 showed a increase from 3 weeks after bone defect formation. The experimental group 2 showed a more increase in healing amount than control group and experimental group 1 from 5 weeks after bone defect formation and the experimental group 2 showed a complete recovery of bone defect at 7 weeks after bone defect formation. Conclusion: The healing process of bone defect is accelerated by rhBMP-2 application in the low calcium diet rats.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.432-437
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• 2008

This paper proposes a defect cell extraction algorithm for TFT-LCD auto-repair system. Auto defect search algorithm and automatic defect cell extraction method are very important for TFT-LCD auto repair system. In the previous literature[1], we proposed an automatic visual inspection algorithm of TFT-LCD. Based on the inspected information(defect size and defect axis, if defect exists) by the automatic search algorithm, defect cells should be extracted from the input image for the auto repair system. For automatic extraction of defect cells, we used a novel block matching algorithm and a simple filtering process in order to find a given reference point in the LCD cell. The proposed defect cell extraction algorithm can be used in all kinds of TFT-LCD devices by changing a stored template which includes a given reference point. Various experimental results show the effectiveness of the proposed method.