• Wind and Structures
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• v.20 no.2
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• pp.315-326
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• 2015

To overcome the drawbacks of the traditional contact-type sensor for structural displacement measurement, the vision-based technology with the aid of the digital image processing algorithm has received increasing concerns from the community of structural health monitoring (SHM). The advanced vision-based system has been widely used to measure the structural displacement of civil engineering structures due to its overwhelming merits of non-contact, long-distance, and high-resolution. However, seldom currently-available vision-based systems are capable of realizing the synchronous structural displacement measurement for multiple points on the investigated structure. In this paper, the method for vision-based multi-point structural displacement measurement is presented. A series of moving loading experiments on a scale arch bridge model are carried out to validate the accuracy and reliability of the vision-based system for multi-point structural displacement measurement. The structural displacements of five points on the bridge deck are measured by the vision-based system and compared with those obtained by the linear variable differential transformer (LVDT). The comparative study demonstrates that the vision-based system is deemed to be an effective and reliable means for multi-point structural displacement measurement.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.333-335
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• 2015

A computer vision-based scene recognition algorithm is proposed for monitoring construction sites. The system analyzes images acquired from a surveillance camera to separate regions and classify them as building, ground, and hole. Mean shift image segmentation algorithm is tested for separating meaningful regions of construction site images. The system would benefit current monitoring practices in that information extracted from images could embrace an environmental context.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.300-306
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• 2000

This paper introduces a new concept of automation for bio-production with tele-operative system. The proposed system showed practical and feasible way of automation for the volatile bio-production process. Based on the proposition, recognition of the job environment with object identification was performed using computer vision system. A man-machine interactive hybrid decision-making, which utilized a concept of tele-operation was proposed to overcome limitations of the capability of computer in image processing and feature extraction from the complex environment image. Identifying watermelons from the outdoor scene of the cultivation field was selected to realize the proposed concept. Identifying watermelon from the camera image of the outdoor cultivation field is very difficult because of the ambiguity among stems, leaves, shades, and especially fruits covered partly by leaves or stems. The analog signal of the outdoor image was captured and transmitted wireless to the host computer by R.F module. The localized window was formed from the outdoor image by pointing to the touch screen. And then a sequence of algorithms to identify the location and size of the watermelon was performed with the local window image. The effect of the light reflectance of fruits, stems, ground, and leaves were also investigated.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.9
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• pp.54-63
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• 1993

Quantization error, generated by the quantization process of an image, is inherent in computer vision. Because, especially in stereo vision, the quantization error in a 2-D image results in position errors in the reconstructed 3-D scene, it is necessary to analyze it mathematically. In this paper, the analysis of the probability density function (pdf) of quantization error for a line-based stereo matching scheme is presented. We show that the theoretical pdf of quantization error in the reconstructed 3-D position information has more general form than the conventional analysis for pixel-based stereo matching schemes. Computer simulation is observed to surpport the theoretical distribution.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.170-173
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• 2001

To apply stereo vision system to obstacle recognition system of AGV, we constructed algorithm of stereo matching and distance measuring with stereo image for positioning of object in area. And using this system, we look into the error between real position and measured position, and studied relationship of compensation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.1049-1050
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• 2013

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.310-310
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• 2000

The main problem in stereo vision is to find corresponding points in left and right image known as correspondence problem. Once correspondences determined, the depth information of those points are easily computed form the pairs of points in both image. In this paper, dynamic programming considering half-occluded region is used fer solving correspondence problem.

• Journal of Korean Port Research
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• v.14 no.3
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• pp.303-312
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• 2000

In this paper, we describe an image processing algorithm which is able to recognize the road lane. This algorithm performs to recognize the interrelation between AGV and the other vehicle. We experimented on AGV driving test with color CCD camera which is setup on the top of vehicle and acquires the digital signal. This paper is composed of two parts. One is image preprocessing part to measure the condition of the condition of the lane and vehicle. This finds the information of lines using RGB ratio cutting algorithm, the edge detection and Hough transform. The other obtains the situation of other vehicles using the image processing and viewport. At first, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, if vehicle knows the driving conditions which are lane angle, distance error and real position of other vehicles, we should calculate the reference steering angle.

• Journal of Biosystems Engineering
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• v.20 no.4
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• pp.368-375
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• 1995

A computer vision system was built to generate images of a stationary egg. This system includes a. CCD camera, a frame grabber, and an incandescent back lighting system An image processing algorithm was developed to accurately detect surface holes and surface cracks on eggs. With 20W of incandescent back light, the detection rate was shown to be the highest. The Sobel operator was found to be the best among various enhancing filters examined. The threshold value to distinguish between the crack and the translucent spots was found to be linear with the average gray level of a whole egg image. Those values of both gray level and area were used as criteria to detect holes in egg and those values of both area and roundness were used to detect cracks in egg. For a sample of 300 eggs, this system was able to correctly analyze an egg for the presence of a defect 97.5% of the time. On the average, it took 59.5 seconds to analyze an egg image and determine whether or not it was defected.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.198-200
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• 2005

Recently, intellectual property problem caused by illegal copy or circulation of digital contents with computer and advance of network. it will lose producer's desire and cause economic losses. so we need to demand ownership protection technology for prevent illegal copy without an owner consent and protect ownership with effect. in this paper, we change digital image at frequency domain and choose a factor choosing frequency area with human perceptibility. we inserted repetitive and adaptive watermark on the whole image by Labview Machine Vision. watermark inserted into the high frequency concentrated textual area with Wavelet Transform and then reduced damage of image by human visual feature after inserted watermark