• Journal of Korea Multimedia Society
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• v.18 no.12
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• pp.1519-1527
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• 2015

TFT-LCD automatic defect inspection system for detecting defects in place of the visual tester does pre-processing, candidate defect pixel detection, and recognition and classification through a blob analysis. An over-detection result of defects acts as an undue burden of blob analysis for recognition and classification. In this paper, we propose defect detection method based on the histogram distribution modeling of TFT-LCD image to minimize over-detection of candidate defective pixels. Primary defect candidate pixels are detected estimating the skewness of the luminance distribution histogram of the background pixels. Based on the detected defect pixels, the defective pixels other than noise pixels are detected using the distribution histogram model of the local area. Experimental results confirm that the proposed method shows an excellent defect detection result on the image containing the various types of defects and the reduction of the degree of over-detection as well.

• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.2
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• pp.28-32
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• 2014

Purpose Patient motion during myocardial perfusion SPECT can produce images that show visual artifacts and perfusion defects. This artifacts and defects remain a significant source of unsatisfactory myocardial perfusion SPECT. Motion correction has been developed as a way to correct and detect the patient motion for reducing artifacts and defects, and each motion correction uses different algorithm. We corrected simulated motion patterns with several motion correction methods and compared those images. Materials and Methods Phantom study was performed. The anthropomorphic torso phantom was made with equal counts from patient's body and simulated defect was added in myocardium phantom for to observe the change in defect. Vertical motion was intentionally generated by moving phantom downward in a returning pattern and in a non-returning pattern throughout the acquisition. In addition, Lateral motion was generated by moving phantom upward in a returning pattern and in a non-returning pattern. The simulated motion patterns were detected and corrected similarly to no-motion pattern image and QPS score, after Motion Detection and Correction Method (MDC), stasis, Hopkins method were applied. Results In phantom study, Changes of perfusion defect were shown in the anterior wall by the simulated phantom motions, and inferior wall's defect was found in some situations. The changes derived from motion were corrected by motion correction methods, but Hopkins and Stasis method showed visual artifact, and this visual artifact did not affect to perfusion score. Conclusion It was confirmed that motion correction method is possible to reduce the motion artifact and artifactual perfusion defect, through the apply on the phantom tests. Motion Detection and Correction Method (MDC) performed better than other method with polar map image and perfusion score result.

• Journal of Korean Neurosurgical Society
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• v.48 no.3
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• pp.213-218
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• 2010

Objective : Pituitary apoplexy (PA) is described as a clinical syndrome characterized by sudden headache, vomiting, visual impairment, and meningismus caused by rapid enlargement of a pituitary adenoma, We retrospectively analyzed the clinical presentation and surgical outcome in PA presenting with cranial neuropathy. Methods : Twelve cases (33%) of PA were retrospectively reviewed among 359 patients diagnosed with pituitary adenoma, The study included 6 males and 6 females, Mean age of patients was 49,0 years, with a range of 16 to 74 years, Follow-up duration ranged from 3 to 20 months, with an average of 12 months, All patients were submitted to surgery, using the transsphenoidal approach (TSA). Results : Symptoms included abrupt headache (11/12), decreased visual acuity (12/12), visual field defect (11/12), and cranial nerve palsy of the third (5/12) and sixth (2/12) Mean height of the mass was 29.0 mm (range 15-46) Duration between the ictus and operation ranged from 1 to 15 days (mean 7.0) The symptom duration before operation and the recovery period of cranial neuropathy correlated significantly (p = 0.0286) TSA resulted in improvement of decreased visual acuity in 91.6%, visual field defect in 54.5%, and cranial neuropathy in 100% at 3 months after surgery. Conclusion : PA is a rare event, complicating 3.3% in our series, Even in blindness following pituitary apoplexy cases, improvement of cranial neuropathy is possible if adequate management is initiated in time, Surgical decompression must be considered as soon as possible in cases with severe visual impairment or cranial neuropathy.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.23 no.2
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• pp.206-209
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• 2010

Objectives : To carry out the oriental medicine treatment on a patient with Functional Bitemporal Hemianopia. Methods : We experienced one case of Functional Bitemporal Hemianopia treated with oriental medical treatment, acupuncture and herbal medication. Results : Visual field defect were improved after treatment. Conclusion : Oriental medical treatment could be safe and effective method in Functional Bitemporal Hemianopia.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2414-2417
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• 2005

Compact Camera Module(CCM) is widely used in PDA, Celluar phone and PC web camera. With the greatly increasing use for mobile applications, there has been a considerable demands for high speed production of CCM. The major burden of production of CCM is assembly of lens module onto CCD or CMOS packaged circuit board. After module is assembled, the CCM is inspected. In this paper, we developed the image capture board for CCM and the imaging processing algorithm to inspect the defects in captured image of assembled CCMs. The performances of the developed inspection system and its algorithm are tested on samples of 10000 CCMs. Experimental results reveal that the proposed system can focus the lens of CCM within 5s and we can recognize various types of defect of CCM modules with good accuracy and high speed.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.254-258
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• 2003

Electronic Speckle Pattern for quantitative evaluation of a impact defect inside of composite material plate are described. The impact on composite material makes inside delamination which is difficult to detect visual inspection and ultrasonic testing due to non-homeogenous structure. This paper proposes the quantitative evaluation technique of defects under real impact. Artificial defects are designed inside of composite plate for development of inspection technique and real defects under impact are inspected and compared with results of visual inspection.

• Smart Structures and Systems
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• v.13 no.6
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• pp.901-925
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• 2014

The reliability of a Bridge management System depends on the quality of visual inspection and the reliable estimation of bridge condition rating. However, the current practices of visual inspection have been identified with several limitations, such as: they are time-consuming, provide incomplete information, and their reliance on inspectors' experience. To overcome such limitations, this paper presents an approach of automating the prediction of condition rating for bridges based on digital image analysis. The proposed methodology encompasses image acquisition, development of 3D visualization model, image processing, and condition rating model. Under this method, scaling defect in concrete bridge components is considered as a candidate defect and the guidelines in the Ontario Structure Inspection Manual (OSIM) have been adopted for developing and testing the proposed method. The automated algorithms for scaling depth prediction and mapping of condition ratings are based on training of back propagation neural networks. The result of developed models showed better prediction capability of condition rating over the existing methods such as, Naïve Bayes Classifiers and Bagged Decision Tree.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6043-6062
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• 2019

Low-rank matrix decomposition has shown its capability in many applications such as image in-painting, de-noising, background reconstruction and defect detection etc. In this paper, we consider the texture background of rail track images and the sparse foreground of the defects to construct a low-rank matrix decomposition model with block sparsity for defect inspection of rail tracks, which jointly minimizes the nuclear norm and the 2-1 norm. Similar to ADM, an alternative method is proposed in this study to solve the optimization problem. After image decomposition, the defect areas in the resulting low-rank image will form dark stripes that horizontally cross the entire image, indicating the preciselocations of the defects. Finally, a two-stage defect extraction method is proposed to locate the defect areas. The experimental results of the two datasets show that our algorithm achieved better performance compared with other methods.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.3
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• pp.129-138
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• 2022

Collecting and labeling sufficient training data, which is essential to deep learning-based visual inspection, is difficult for manufacturers to perform because it is very expensive. This paper presents a steel plate surface defect detection system with industrial-grade detection performance by training a small amount of steel plate surface images consisting of labeled and non-labeled data. To overcome the problem of lack of training data, we propose two data augmentation techniques: program-based augmentation, which generates defect images in a geometric way, and generative model-based augmentation, which learns the distribution of labeled data. We also propose a 4-step semi-supervised learning using pseudo labels and consistency training with fixed-size augmentation in order to utilize unlabeled data for training. The proposed technique obtained about 99% defect detection performance for four defect types by using 100 real images including labeled and unlabeled data.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.101.6-101
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• 2001

This paper deals with inspect algorithm using visual system. One of the major problems that arise during polymer production is the estimation of the noise of the product(bad pallets). An erroneous output can cause a lot of losses (production and financial losses). Therefore new methods for real-time inspection of the noise are demanded. For this reason, we have presented a development of vision system algorithm for the defect inspection of PE pallets. First of all, in order to detect the edge of object, the differential filter is used. And we apply to the labeling algorithm for feature extraction. This algorithm is designed for the defect inspection of pallets ...