• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.661-662
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• 2007

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.671-674
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• 2005

Atmospheric correction over the ocean part is more important than that over the land because the signal from the ocean is very small about one tenth of that reflected from land. In this study, the Spectral Shape Matching Method (SSMM) developed by Ahn and Shanmugam (2004) is evaluated using Landsat imagery acquired over the highly turbid Saemangeum Coastal Area. The result of SSMM is compared with COST model developed by Chavez (1991 and 1997). In principle, SSMM is simple and easy to implement on any satellite imagery, relying on both field and image properties. To assess the potential use of these methods, several field campaigns were conducted in the Saemangeum coastal area corresponding with Landsat-7 satellite's overpass on 29 May 2005. In-situ data collected from the coastal waters of Saemangeum using optical instruments (ASD field spectroradiometer) consists of ChI, Ap, SS, aooM, F(d). In order to perform SSMM, we use the in-situ water-leaving radiance spectra from clear oceanic waters to estimate the the path radiance from total signal recorded at the top of the atmosphere (TOA), due to the reason that the shape of clear water-leaving radiance spectra is nearly stable than turbid water-leaving radiance spectra. The retrieved water-leaving radiance after subtraction of path signal from TOA signal in this way is compared with that estimated by COST model. The result shows that SSMM enabled retrieval of water-leaving radiance spectra that are consistent with in-situ data obtained from Saemangeum coastal waters. The COST model yielded significantly high errors in these areas.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.185-191
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• 1999

Mathematical morphology based on set theory has been applied to various areas in image processing. Pitas proposed a object recognition algorithm using Morphological Shape Decomposition(MSD), and a new representation scheme called Morphological Shape Representation(MSR). The Pitas's algorithm is a simple and adequate approach to recognize objects that are rotated 45 degree-units with respect to the model object. However, this recognition scheme fails in case of random rotation. This disadvantage may be compensated by defining small angle increments. However, this solution may greatly increase computational complexity because the smaller the step makes more number of rotations to be necessary. In this paper, we propose a new method for object recognition based on MSD. The first step of our method decomposes a binary shape into a union of simple binary shapes, and then a new tree structure is constructed which ran represent the relations of binary shapes in an object. finally, we obtain the feature informations invariant to the rotation, translation, and scaling from the tree and calculate matching scores using efficient matching measure. Because our method does not need to rotate the object to be tested, it could be more efficient than Pitas's one. MSR has an intricate structure so that it might be difficult to calculate matching scores even for a little complex object. But our tree has simpler structure than MSR, and easier to calculated the matchng score. We experimented 20 test images scaled, rotated, and translated versions of five kinds of automobile images. The simulation result using octagonal structure elements shows 95% correct recognition rate. The experimental results using approximated circular structure elements are examined. Also, the effect of noise on MSR scheme is considered.

• Journal of the Earthquake Engineering Society of Korea
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• v.15 no.5
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• pp.1-10
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• 2011

This paper proposes an efficient method for selecting ground motions with the mean response spectrum matching a target spectrum. Since former studies reported that the shape and amplitude of the response spectra can be treated independently for selecting ground motions, this study first selects ground motions such that the shape of their mean response spectrum matches that of the target spectrum, then scales the ground motions. To select the ground motions best matching the shape of the target response spectrum, the standard deviation of the difference between the target response spectrum and the mean response spectrum of the selected ground motions needs to be minimized. Unlike the existing procedure, the scaling factor can be computed without iteration. Based on the selection results of 7 ground motions from a library of 40 ground motions, the proposed method is verified as an accurate and efficient method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.601-605
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• 2009

We have proposed a measurement system for measuring a whole shape of an object easily. The proposed system consists of a camera and a cylinder whose inside is coated by a mirror layer. A target object is placed inside the cylinder and an image is captured by the camera from right above. The captured image includes sets of points that are observed from multiple viewpoints: one is observed directly, and others are observed via the mirror. Therefore, the whole shape of the object can be measured using stereo vision in a single shot. This paper shows that a prototype of the proposed system was implemented and an actual object was measured using the prototype. A method based on a pattern matching which uses a value of SSD (Sum of Squared Difference), and a method based on DP (Dynamic Programming) are employed to identify a set of corresponding points in warped captured images.

• Korean Journal of Human Ecology
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• v.23 no.6
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• pp.1171-1189
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• 2014

In order to provide the basic data for creating the environment which can efficiently reflect prefer fit along with body size when selecting clothes size in the indirect purchasing environment, this study analyzed the difference of ready-made jacket part-specific fit preferred by fashion models in their twenties and female college students. This study was to analyze the impact of body size, recognition of body part-specific characteristics shape, body satisfaction on prefer fit of jacket. As for the difference of prefer fit depending on the body size, female college students preferred more loose fit than models. The difference according to recognition of body part-specific characteristics shape turned out to be significant for prefer fit depending on the degree of bend of neck, arm length, bend of back recognition and matching fit was found to be preferred as they recognize their body shape to be normal and the difference according to body satisfaction appeared to be significant in the terms of bend of back, hip width/protrusion, torso size/length, sleeve length, whole body shape and they turned out to prefer matching fit as they are satisfied with their body. As shown above, body size, recognition of body part-specific characteristics shape, especially body satisfaction have a great influence on prefer fit of jacket and therefore, if preparing for a size selection step according to body shape and satisfaction in the jacket size selection process, customers' satisfaction in jacket size may be improved and it is considered to be helpful for both consumers and sellers.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.174-177
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• 2009

In object tracking, the template matching methods have been developed and frequently used. It is fast enough, but not robust to an object with the variation of size and shape. In order to overcome the limitation of the template matching method, this paper proposes a template update technique. After finding an object position using the correlation-based adaptive predictive search, the proposed method selects blocks which contain object's boundary. It estimates the motion of boundary using block matching, and then updates template. We applied it to IR image sequences including an approaching object. From the experimental results, the proposed method showed successful performance to track object.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.311-311
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• 2000

We propose a DP-based formulation for matching line patterns by defining a robust and stable geometric representation that is based on the conceptual organizations. Usually, the endpoint proximity and collinearity of image lines, as two main conceptual organization groups, are useful cues to match the model shape in the scene. As the endpoint proximity, we detect junctions from image lines. We then search for junction groups by using geometric constraint between the junctions. A junction chain similar to the model chain is searched in the scene, based on a local comparison. A Dynamic Programming-based search algorithm reduces the time complexity for the search of the model chain in the scene. Our system can find a reasonable matching, although there exist severely distorted objects in the scene. We demonstrate the feasibility of the DP-based matching method using both synthetic and real images.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.573-576
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• 1999

This paper presents a new shape segmentation algorithm. The procedure to achieve complete segmentation consists of two steps : the first step is mapping shape into two dimension by the using Distance Transform, the second step is partitioning the region by using the Watershed algorithm. As a application of the proposed algorithm, we perform the matching experiment for several objects by the use of segmented region. Simulation results demonstrate the efficiency of the proposed method, and the method has scale, rotation, and shift invariant properties.

• Communications for Statistical Applications and Methods
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• v.15 no.4
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• pp.543-549
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• 2008

Inspired by using a robust loss function in the support vector machine regression to control training error and the idea of robust template matching with M-estimator, Chen (2004) applies M-estimator techniques to gaussian radial basis functions and form a new class of robust kernels for the support vector machines. We are specially interested in the shape of the Huber's M-estimator in this context and propose a way to find the shape parameter of the Huber's M-estimating function. For simplicity, only the two-class classification problem is considered.