• International conference on construction engineering and project management
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• 2022.06a
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• pp.912-919
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• 2022

The study is an image-based assessment that uses image processing techniques to determine the condition of concrete with surface cracks. The preparations of the dataset include resizing and image filtering to ensure statistical homogeneity and noise reduction. The image dataset is then segmented, making it more suited for extracting important features and easier to evaluate. The image is transformed into grayscale which removes the hue and saturation but retains the luminance. To create a clean edge map, the edge detection process is utilized to extract the major edge features of the image. The Otsu method is used to minimize intraclass variation between black and white pixels. Additionally, the median filter was employed to reduce noise while keeping the borders of the image. Image processing techniques are used to enhance the significant features of the concrete image, especially the defects. In this study, the tonal zones of the histogram and its properties are used to analyze the condition of the concrete. By examining the histogram, the viewer will be able to determine the information on the image through the number of pixels associated and each tonal characteristic on a graph. The features of the five tonal zones of the histogram which implies the qualities of the concrete image may be evaluated based on the quality of the contrast, brightness, highlights, shadow spikes, or the condition of the shadow region that corresponds to the foreground.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1120-1131
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• 2016

In this paper, we propose a smoker recognition algorithm, detecting smokers in a video sequence in order to prevent fire accidents. We use description-based method in hierarchical approaches to recognize smoker's activity, the algorithm consists of background subtraction, object detection, event search, event judgement. Background subtraction generates slow-motion and fast-motion foreground image from input image using Gaussian mixture model with two different learning-rate. Then, it extracts object locations in the slow-motion image using chain-rule based contour detection. For each object, face is detected by using Haar-like feature and smoke is detected by reflecting frequency and direction of smoke in fast-motion foreground. Hand movements are detected by motion estimation. The algorithm examines the features in a certain interval and infers that whether the object is a smoker. It robustly can detect a smoker among different objects while achieving real-time performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.796-804
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• 2002

This paper presents a new algorithm of fingerprint image analysis and processing using directional filter bank(DFB). The directional components of ridge is very important in pre-processing steps of fingerprint image processing such as image enhancement by directional filtering followed by estimationg the directional image of ridge patterns. The DFB analyzes input image into directional subband images and synthesizes them to the perfectly reconstructed image. In this paper, a new fingerprint processing algorithm using the DFB is proposed. The algorithm decomposes the fingerprint image into directional subband images and performs directional map generation, foreground segmentation, singular points extraction and image enhancement based on local directional energy estimate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.149-152
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• 2016

In this paper, we propose an algorithm to track human body of input video from a single camera. The proposed method gets the difference image between gray image of input image and one of background image and also the difference image between hue image of input image and one of background image. Then we combine the results, splits foreground and background and detect human body objects. Then each object is numbered and is tracked. The proposed method tracks each object using the intensity and hue histogram of local area in objects. The proposed method is applied to video from a camera and tracked well the hided objects and the overlapped objects.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.11a
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• pp.237-238
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• 2013

The quality of document image captured from electronic display might be worse when it is compared with document image captured from paper. The problem appears because of Moir? noise. This problem can lead to achieve inaccurate intermediate result for further image processing. This paper proposes a method to remove Moir? noise of document images captured from electronic display. The proposed algorithm is separated in two parts. In the first step, it corrects the text area region (foreground) with small area of smoothing. Then, it corrects the background area with large area of smoothing.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1093-1096
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• 1999

In this paper, video image segmentation algorithm based on color histogram and change detector is proposed. Color histograms are calculated from both changed region which is detected in the previous and current frame and unchanged region. With each histogram, modes and valleys are detected. Then, color vectors are calculated by averaging pixels in modes. Markers are extracted by labeling color vectors that represent modes, the watershed algorithm is applied to determine uncertain region. In growing region, the root mean square(RMS) of the distance between average pixel in marker region and adjacent pixel is used as a measure. The proposed algorithm based on color histogram and change detector segments video image fastly and effectively. And simulation results show that the proposed method determines the exact boundary between background and foreground.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.569-572
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• 2002

In this study, a real-time image composition system was implemented using chroma key algorithm. To write a high Quality chroma key function based on processing of foreground and/or background frames before combining them into an output image, Adaptive 3-dimensional surface equation model was proposed. When the bright of room is changed or shadow of object is on the blue screen, proposed algorithm would still produce good result.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11a
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• pp.270-273
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• 2001

Electrical tree is studied widely by manufacture state of insulating material fare and blazing fire diagnosis system of use in phenomenon of part discharge that happen for main cause of dielectric breakdown of equipment for electric power. Use process that draw tree pattern here measuring above zero to study special quality of this electricity tree, real-time processing by image processing is proposed because reproduction of tree blazing fire process drops and pattern of tree is difficult correct quantification of tree growth by existent visual observation by involution. This research presents general process that need in image processing of tree blazing fire, and that remove various noises that happen in above zero by measuring electrical tree dividing background and complete view in measured above zero taking advantage of specially proposed complete view object abstraction techniques effectively and quantification of tree becomes easy naturally, can apply to dielectric breakdown estimate because can chase growth process of tree.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.2
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• pp.81-87
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• 2013

Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter (AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1944-1947
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• 2003

In this paper, we propose a dynamic-based compression system by creating mosaic background and transmitting the change information. A dynamic mosaic of the background is progressively integrated in a single image using the camera motion information. For the camera motion estimation, we calculate affine motion parameters for each frame sequentially with respect to its previous frame. The camera motion is robustly estimated on the background by discriminating between background and foreground regions. The modified block-based motion estimation is used to separate the back-ground region.