• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.31 no.3
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• pp.105-109
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• 1999

The purpose of this experiment was to see the effect of local basis weight on the local strain during changing moisture content in handsheets. The averaged strain value of the whole size of paper sheet did not give more valuable information to explain non uniform deformation in the paper sheet. The combination of intact strain measurement system KISA (Linear Image Strain Analysis) and local basis weight measurement method using a scanner made it possible to compare local basis weight with local strain to explain moisture induced paper deformation . Usually higher basis weight local area showed higher moisture induced local strain. However, the hygro-induced strain values were highly affected by the behavior of neighbor local areas. Well distributed local basis weight paper would give more uniform local strains than those of non-uniformed local basis weight paper.

• Journal of Korean Society of Rural Planning
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• v.15 no.2
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• pp.59-68
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• 2009

Nowadays, local governments have been developing an image to represent their regions' identity. These characters contain unlimited capabilities of utilization and advertising effect that adds to their high value. However, we must consider how effectively the image helps in representing its region because some characters have been produced upon timely basis without consistent long-term planning. This study is to investigate the image and motif of the local government characters from the consumer's perspective. The results are as follows: 1)The images employed by the local governments are not highly preferred and most regions select motifs from their local agricultural products and native plants. 2)The variables that affect the character of the local governments are such as beauty, identity, etc. In conclusion, in order to maximize the local government image, one must improve the design concepts, encourage advertisement of regional festivities and travel commercialization, and advocate the identity and beauty of the local area to the residents and other regional people.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2006.06a
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• pp.251-257
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• 2006

The performance of face recognition methods using subspace projection is directly related to the characteristics of their basis images, especially in the cases of local distortion or partial occlusion. In order for a subspace projection method to be robust to local distortion and partial occlusion, the basis images generated by the method should exhibit a part-based local representation. We propose an effective part-based local representation method named locally salient ICA (LS-ICA) method for face recognition that is robust to local distortion and partial occlusion. The LS-ICA method only employs locally salient information from important facial parts in order to maximize the benefit of applying the idea of 'recognition by parts.' It creates part-based local basis images by imposing additional localization constraint in the process of computing ICA architecture I basis images. We have contrasted the LS-ICA method with other part-based representations such as LNMF (Localized Non-negative Matrix Factorization)and LFA (Local Feature Analysis). Experimental results show that the LS-ICA method performs better than PCA, ICA architecture I, ICA architecture II, LFA, and LNMF methods, especially in the cases of partial occlusions and local distortion

• Archives of design research
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• v.16 no.1
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• pp.63-72
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• 2003

The purpose of this study is to understand the character of concerned local area through using roadside space that is space for daily experience of citizen as target, extracting symbolic image reconsidering the historical and cultural character and clarifying the local identity on the basis of it. Through applying image of local symbolism and future-oriented roadside to street furniture, I tried to express local symbolism and through composing symbolic roadside of local that can be newly recognized as unique street, I tried to give a local symbolism and compose active roadside environment. Through providing basic material and actual design example, this paper tried to activate characterized local culture. As the method to approach design of symbolic roadside, the researcher divided local symbolic image into present local image and future-oriented image through selecting the roadside that historical element is lost and urbanization is achieved as target. The researcher characterized local roadside, using street furniture as symbolic tool of future-oriented roadside on the basis of symbolic image extracted from image evaluation testing. This paper has the meaning to suggest one direction for extracting symbolism when organizing distinguished roadside through applying symbolic image to roadside environmental facility, helping for of local resident's sense of place, his self-esteem and love for his hometown and public authority's establishing and promoting the policy concerned to the context of this paper.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.9
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• pp.1167-1174
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• 1999

In this paper, we present a new technique for the local decomposition of convex structuring elements for morphological image processing. Local decomposition of a structuring element consists of local structuring elements, in which each structuring element consists of a subset of origin pixel and its eight neighbors. Generally, local decomposition of a structuring element reduces the amount of computation required for morphological operations with the structuring element. A unique feature of our approach is the use of linear integer programming technique to determine optimal local decomposition that guarantees the minimal amount of computation. We defined a digital convex polygon, which, in turn, is defined as a convex structuring element, and formulated the necessary and sufficient conditions to decompose a digital convex polygon into a set of basis digital convex polygons. We used a set of linear equations to represent the relationships between the edges and the positions of the original convex polygon, and those of the basis convex polygons. Further. a cost function was used represent the total processing time required for computation of dilation/erosion with the structuring elements in a decomposition. Then integer linear programming was used to seek an optimal local decomposition, that satisfies the linear equations and simultaneously minimize the cost function.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.617-623
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• 2008

This paper presents a human motion recognition method using both centroid shift and local basis images. The centroid shift based on 1st moment balance technique is applied to get the robust motion images against position or size changes, the extraction of local basis images based on independent component analysis(ICA) is also applied to find a set of statistically independent motion features, which is included in each motions. Especially, ICA of fixed-point(FP) algorithm based on Newton method is used for being quick to extract a local basis images of motions. The proposed method has been applied to the problem for recognizing the 160(1 person * 10 animals * 16 motions) sign language motion images of 240*215 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed method has a superior recognition performances(speed, rate) than the method using local eigen images and the method using local basis images without centroid shift respectively.

• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.197-205
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• 2014

As computer vision algorithms are developed on a continuous basis, the visual information from vision sensors has been widely used in the context of simultaneous localization and mapping (SLAM), called visual SLAM, which utilizes relative motion information between images. This research addresses a visual SLAM framework for online localization and mapping in an unstructured seabed environment that can be applied to a low-cost unmanned underwater vehicle equipped with a single monocular camera as a major measurement sensor. Typically, an image motion model with a predefined dimensionality can be corrupted by errors due to the violation of the model assumptions, which may lead to performance degradation of the visual SLAM estimation. To deal with the erroneous image motion model, this study employs a local bundle optimization (LBO) scheme when a closed loop is detected. The results of comparison between visual SLAM estimation with LBO and the other case are presented to validate the effectiveness of the proposed methodology.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.9
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• pp.1531-1540
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• 2016

In this paper, we propose vehicle license plate recognition system based on Radial Basis Function Neural Networks (RBFNNs) with the use of local binarization functions and canny edge algorithm. In order to detect the area of license plate and also recognize license plate numbers, binary images are generated by using local binarization methods, which consider local brightness, and canny edge detection. The generated binary images provide information related to the size and the position of license plate. Additionally, image warping is used to compensate the distortion of images obtained from the side. After extracting license plate numbers, the dimensionality of number images is reduced through Principal Component Analysis (PCA) and is used as input variables to RBFNNs. Particle Swarm Optimization (PSO) algorithm is used to optimize a number of essential parameters needed to improve the accuracy of RBFNNs. Those optimized parameters include the number of clusters and the fuzzification coefficient used in the FCM algorithm, and the orders of polynomial of networks. Image data sets are obtained by changing the distance between stationary vehicle and camera and then used to evaluate the performance of the proposed system.

• The Journal of the Acoustical Society of Korea
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• v.18 no.3E
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• pp.37-43
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• 1999

In this paper, we present a new technique for the optimal local decomposition of convex structuring elements on a hexagonal grid, which are used as templates for morphological image processing. Each basis structuring element in a local decomposition is a local convex structuring element, which can be contained in hexagonal window centered at the origin. Generally, local decomposition of a structuring element results in great savings in the processing time for computing morphological operations. First, we define a convex structuring element on a hexagonal grid and formulate the necessary and sufficient conditions to decompose a convex structuring element into the set of basis convex structuring elements. Further, a cost function was defined to represent the amount of computation or execution time required for performing dilations on different computing environments and by different implementation methods. Then the decomposition condition and the cost function are applied to find the optimal local decomposition of convex structuring elements, which guarantees the minimal amount of computation for morphological operation. Simulation shows that optimal local decomposition results in great reduction in the amount of computation for morphological operations. Our technique is general and flexible since different cost functions could be used to achieve optimal local decomposition for different computing environments and implementation methods.

• Journal of Korea Multimedia Society
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• v.16 no.11
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• pp.1250-1260
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• 2013

The contrast enhancement techniques based on Laplacian pyramid image fusion have a benefit that they can faithfully describe the image information because they combine the multiple resource images by selecting the desired pixel in each image. However, they also have some problem that the output image may contain noise, because the methods evaluate the visual information on the basis of each pixel. In this paper, an improved contrast enhancement method, which effectively suppresses the noise, using image fusion is proposed. The proposed method combines the resource images by making Laplacian pyramids generated from weight maps, which are produced by measuring the difference between the block-based local well exposedness and local homogeneity for each resource image. We showed the proposed method could produce less noisy images compared to the conventional techniques in the test for various images.