• Proceedings of the Korean Society of Computer Information Conference
• /
• 2021.01a
• /
• pp.69-70
• /
• 2021

본 논문은 PPM으로 관리되고 있는 자동차 부품 제조 공정에서 검사자의 육안검사 방법을 대체하기 위해 머신비전 및 CNN 기반 불량 검출 시스템으로 제안되었던 방식들의 단점을 개선하기 위하여 기존 머신 비전 기술에 합성곱 오토인코더 모델을 적용하여 단점을 해결하였다. 본 논문에서 제시한 오토인코더를 이용하는 방법은 정상 생산품의 이미지만으로 학습을 진행하고, 학습된 모델은 불량 부위가 포함된 이미지를 입력받아 정상 이미지로 출력한다. 이 방법을 사용하여 불량의 부위와 크기를 알 수 있었으며 불량 여부의 판단은 임계치에 의한 불량 부위의 화소 수 계산으로 판단하였다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2004.04b
• /
• pp.697-699
• /
• 2004

LCD의 생산이 많아짐에 따라 LCD의 불량 검출이 중요해 지고 있다. 불랑 검사는 눈으로 확인할 수 있는 범위에서 검사가 이루어지고 있으며, 만약 눈으로 식별이 불가능한 경우 적외선 카메라나 초음파 센서를 사용하여 검사가 이루어진다. 본 논문에서는 카메라를 이용하여 LCD 패널의 표면에 있는 불량 검출을 위하여 각 Dot에 대한 R, G, B 값을 추출한 후, 추출된 픽셀을 제안된 알고리즘에 적용하여 불량을 검출하는 것을 목적으로 하고 있다.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.6
• /
• pp.3416-3422
• /
• 2014

A shock absorber rod is located in the center of the absorber piston and is responsible for the reciprocating movement portion. If it has surface defects, the damping performance of product will be adversely affected. A rod surface has gloss by heat treatment. Therefore, it is difficult to find a defect, such as dust, imprints, and blowholes. Because a total inspection is achieved by visual inspection by workers, it causes eyestrain and the quality of the product is not constant. In this paper, a machine vision system was developed to find a defect using a line-scan camera. The machine can detect surface defects than 0.3mm. To minimize the occurrence probability of defects on the inspection process, the developed auto inspection system had an automatic feeding system and incorporated a protection system. Through the development of this system, which relies on the operator's visual inspection of the surface of the shock absorber, the Rod inspection system constructed quality inspection standards and standardized tests to ensure improved reliability.

• Smart Media Journal
• /
• v.11 no.9
• /
• pp.47-55
• /
• 2022

Quality control in the smart factory manufacturing process is an important factor. Currently, quality inspection of home appliance manufacturing parts produced by the mold process is mostly performed with the naked eye of the operator, resulting in a high error rate of inspection. In order to improve the quality competition, an automatic defect detection system was designed and implemented. The proposed system acquires an image by photographing an object with a high-performance scan camera at a specific location, and reads defective products due to scratches, dents, and foreign substances according to the vision inspection algorithm. In this study, the depth-based branch decision algorithm (DBD) was developed to increase the recognition rate of defects due to scratches, and the accuracy was improved.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.16 no.3
• /
• pp.123-128
• /
• 2016

In manufacturing processing of a secondary battery, the visual inspection system is studied and developed to check the surface defects of the electrode plates. It consists of two parts, one is the hardware control and the other software implementation. The former is made up to the system configuration and the design of the optical system, the illuminations and the controllers. The latter is the detection algorithms of the surface defects. This system achieves the quality improvement of the electrode process and the price competitiveness. By using the proposed defects detection algorithms this system demonstrates the high reliability of spot, line, manhole, extraneous substance, scratch, and crater defect of a electrode plate surface.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.8 no.3
• /
• pp.403-408
• /
• 2013

In this paper, we propose to develop an inspection system that recognizes surface cracks on the brake pad and the types of brake pads of each car during the production process, on a conveyor belt. The brake pad is made from a mixture of materials, using high-heat and pressure. Therefore, the brake pad can be cracked and damaged on the surface during production. Our goal is to develop an effective detection system and application software to detect substandard product. A shadow is generated when the artificial light shines on the damaged of the surface of pad. Using the computer vision algorithm that is proposed we can detect the substandard product. Results from experiments confrim the performance of the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.7
• /
• pp.1737-1742
• /
• 2015

In the industrial field for product inspection needs not only on the surface of the product but also the internal components defect inspection. Generally, optical inspection is mainly used for item inspection from production process. However, this is only to check defect of surface it is difficult to perform inspection of goods internal. To overcome these limitations, Instead of optical device by using the portable X- ray DR image acquisition device system developed to obtain an image in real time at the same time and determine product defects. After obtaining the X- ray image, the inspection product within error range is passed after machine image processing. Also, the results and numbers are stored by users.

• Journal of Food Hygiene and Safety
• /
• v.23 no.3
• /
• pp.191-197
• /
• 2008

This work was intended for the identification of markers that are found only in the spoiled red pepper powder. When analyzed by GC/MASS, the spoiled red pepper powder contains characteristic naphthalene derivatives, 1, 2, 3, 5, 6, 7, 8, $8\alpha$-octahydro-1, $8\alpha$-dimethyl-7-(1-methylethenyl)-naphthalene and 2-isopropenyl-$4\alpha$, 8-dimethyl-1, 2, 3, 4, $4\alpha$, 5, 6, $8\alpha$-octahydronaphthalene, which have not found in the normal red pepper powder. In addition, microscopic observation and microbial enumeration of the red pepper powder had been performed. Images by scanning electron microscopy showed that the surfaces of spoiled pepper powder were rough with many kinds of microbes, compared with those of normal red pepper powder. A good correlation between the bacterial and fungal counts in the same sample was observed and could be clearly classified into two groups, the normal and the spoiled group, by difference in the microbial counts. These results suggest that the spoiled red pepper powder can be identified by a combination of GC/MASS, microbial counts, and scanning electron microscopy.

• Journal of the Korea Convergence Society
• /
• v.8 no.12
• /
• pp.23-29
• /
• 2017

This paper introduces the mold technology for the development of ultra-compact package of less than 1mm, and also analyze the error pattern of the results using this mold technology. The existing ultra-small mold structure was one-piece, which caused the surface of EDM to be rough and increase the error rate. This has been an obstacle to further reducing the size of the mold. On the other hand, the proposed mold technology tries to overcome the limitation of the one-piece type by using the prefabricated type method. This paper also classify defect patterns in the results of the proposed mold structure and analyze the occurrence probability of each pattern to use as a basic data to develop a detector.

• Journal of the Semiconductor & Display Technology
• /
• v.12 no.2
• /
• pp.57-61
• /
• 2013

This paper presents adaptive neuro-fuzzy inference based defect detection method for various defect types, such as micro-crack, fingerprint and contamination, in heterogeneously textured surface of polycrystalline solar wafers. Polycrystalline solar wafer consists of various crystals so the surface of solar wafer shows heterogeneously textures. Because of this property the visual inspection of defects is very difficult. In the proposed method, we use local binary feature and fuzzy reasoning for defect detection. Experimental results show that our proposed method achieves a detection rate of 80%~100%, a missing rate of 0%~20% and an over detection (overkill) rate of 9%~21%.