• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.25-32
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• 2018

In this paper, we propose an edge detection algorithm for auto focus of infrared camera. We designed and implemented the edge detection of infrared image by using a spatial filter on FPGA. The infrared camera should be designed to minimize the image processing time and usage of hardware resource because these days surveillance systems should have the fast response and be low size, weight and power. we applied the $3{\times}3$ mask filter which has an advantage of minimizing the usage of memory and the propagation delay to process filtering. When we applied Laplacian filter to extract contour data from an image, not only edge components but also noise components of the image were extracted by the filter. These noise components make it difficult to determine the focus state. Also a bad pixel of infrared detector causes a problem in detecting the edge components. So we propose an adaptive edge detection filter that is a method to extract only edge components except noise components of an image by analyzing a variance of pixel data in $3{\times}3$ memory area. And we can detect the bad pixel and replace it with neighboring normal pixel value when we store a pixel in $3{\times}3$ memory area for filtering calculation. The experimental result proves that the proposed method is effective to implement the edge detection for auto focus in infrared camera.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1224-1227
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• 2002

In this paper, we propose a composition method of the template image whose detection performance does not have incorrect detection and improves also on the tough photography conditions of the outdoors, rainy weather and night. This research was done to measure a relative position between a spreader and a target container with image processing to realize full-automatic quayside gantry cranes. By the proposal method, we confirmed that the template image for object detection has a contour image more effective than a gray image.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2327-2330
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• 2003

This paper deals with face detection and recognition using ellipsodal information and wavelet packet analysis. We proposed two methods. First, Face detection method uses general ellipsodal information of human face contour and we find eye position on wavelet transformed face images A novel method for recognition of views of human faces under roughly constant illumination is presented. Second, The proposed Face recognition scheme is based on the analysis of a wavelet packet decomposition of the face images. Each face image is first located and then, described by a subset of band filtered images containing wavelet coefficients. From these wavelet coefficients, which characterize the face texture, the Euclidian distance can be used in order to classify the face feature vectors into person classes. Experimental results are presented using images from the FERET and the MIT FACES databases. The efficiency of the proposed approach is analyzed according to the FERET evaluation procedure and by comparing our results with those obtained using the well-known Eigenfaces method. The proposed system achieved an rate of 97％(MIT data), 95.8％(FERET databace)

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.277-280
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• 2007

A moving object tracking algorithm for image searching based on specific color detection is proposed in this paper. That is preprocessed for a luminance variation and noise cancellation to be robust system. The motion tracking is used the difference between input image and reference image in R, G, B each channels for a moving image. The proposed method is enhanced to 15% fast in comparison with the contour tracking method and the matching method, and stable.

• Journal of the Semiconductor & Display Technology
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• v.15 no.3
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• pp.51-56
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• 2016

This paper proposes a new image enhancement method for an infrared thermal image. The proposed method uses both Laplacian and Prewitt edge detectors. Without a visible light, it uses an infrared image for the edge detection. The method subtracts contour images from the infrared thermal image. It results black contours of objects in the infrared thermal image. That makes the objects in the infrared thermal image distinguished clearly. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using various infrared thermal images. The results show that the proposed method is successful for image enhancement of an infrared thermal image.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10a
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• pp.767-770
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• 2001

Edge detection is one of issues with essential importance in the area of image process. An edge in image is a boundary or contour which a significant change occurs in image intensity. In the paper, we process edge detection algorithms which are based on Potts automata. The dynamical behavior of these automata is completely determined by Lyapunov operators for sequential and parallel update. If Potts Automata convergence to fixed points, then it can be used to image processing. From the generalized Potts automata point of view, we propose a Potts Automata technique for detecting edge. Based on the experimental results we discuss the advantage and efficiency.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.5
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• pp.39-46
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• 2007

Research on human identification in ubiquitous environment has recently attracted a lot of attention. As one of those research, gait recognition is an efficient method of human identification using physical features of a walking person at a distance. In this paper, we present a human shape extraction and tracking for gait recognition using geodesic active contour models(GACMs) combined with mean shift algorithm The active contour models (ACMs) are very effective to deal with the non-rigid object because of its elastic property. However, they have the limitation that their performance is mainly dependent on the initial curve. To overcome this problem, we combine the mean shift algorithm with the traditional GACMs. The main idea is very simple. Before evolving using level set method, the initial curve in each frame is re-localized near the human region and is resized enough to include the targe region. This mechanism allows for reducing the number of iterations and for handling the large object motion. The proposed system is composed of human region detection and human shape tracking modules. In the human region detection module, the silhouette of a walking person is extracted by background subtraction and morphologic operation. Then human shape are correctly obtained by the GACMs with mean shift algorithm. In experimental results, the proposed method show that it is extracted and tracked efficiently accurate shape for gait recognition.

• Journal of KIISE:Software and Applications
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• v.27 no.7
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• pp.731-741
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• 2000

This paper proposes a method to detect a facial region and extract facial features which is crucial for visual recognition of human faces. In this paper, we extract the MER(Minimum Enclosing Rectangle) of a face and facial components using projection analysis on both edge image and binary image. We use an active contour model(snakes) for extraction of the contours of eye, mouth, eyebrow, and face in order to reflect the individual differences of facial shapes and converge quickly. The determination of initial contour is very important for the performance of snakes. Particularly, we detect Minimum Enclosing Rectangle(MER) of facial components and then determine initial contours using general shape of facial components within the boundary of the obtained MER. We obtained experimental results to show that MER extraction of the eye, mouth, and face was performed successfully. But in the case of images with bright eyebrow, MER extraction of eyebrow was performed poorly. We obtained good contour extraction with the individual differences of facial shapes. Particularly, in the eye contour extraction, we combined edges by first order derivative operator and zero crossings by second order derivative operator in designing energy function of snakes, and we achieved good eye contours. For the face contour extraction, we used both edges and grey level intensity of pixels in designing of energy function. Good face contours were extracted as well.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.569-584
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• 2009

Edge detection in images has been widely used in image processing system and computer vision. Morphological edge detection has used structuring elements with fixed shapes. This paper presents morphological operators with non-fixed shape kernels, or amoebas, which take into account the image contour variations to adapt their shape. Experimental results are analyzed in both qualitative analysis through visual inspection and quantitative analysis with PFOM and ROC curves. The Experiments demonstrate that these novel operators outperform classical morphological operations with a fixed, space-invariant structuring elements for edge detection applications.

• Structural Engineering and Mechanics
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• v.39 no.1
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• pp.77-91
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• 2011

A simply structural damage detection software is developed to identification damage in beams. According to linear fracture mechanics theory, the localized additional flexibility in damage vicinity can be represented by a lumped parameter element. The damaged beam is modeled by wavelet-based elements to gain the first three frequencies precisely. The first three frequencies influencing functions of damage location and depth are approximated by means of surface-fitting techniques to gain damage detection database of forward problem. Then the first three measured natural frequencies are employed as inputs to solve inverse problem and the intersection of the three frequencies contour lines predict the damage location and depth. The DLL (Dynamic Linkable Library) file of damage detection method is coded by C++ and the corresponding interface of software is coded by virtual instrument software LabVIEW. Finally, the software is tested on beams and shafts in engineering. It is shown that the presented software can be used in actual engineering structures.