• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.521-524
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• 2005

This paper proposes a fusion algorithm which merges multiple vein pattern images into a single image, larger than those images. As a preprocessing step of template matching, during the verification of biometric data such as fingerprint image, vein pattern image of hand, etc., the fusion technique is used to make reference image larger than the candidate images in order to enhance the matching performance. In this paper, a new algorithm, called BSA (Boundary Stitching Algorithm) is proposed, in which the boundary rectilinear parts extracted from the candidate images are stitched to the reference image in order to enlarge its matching space. By applying BSA to practical vein pattern verification system, its verification rate was increased by about 10%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11C
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• pp.898-904
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• 2008

In this paper, we propose a fast algorithm to generate the array of elemental image in a computer generated integral imaging system. It generates the array of elemental image using depth information, needs less computing time to produce the result by using the concept of boundary area and computing the voxel within boundary area. By comparing the computing time of proposed algorithm with that of the existing algorithm theoretically and experimently, we proved the efficiency of this algorithm.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.2
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• pp.259-269
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• 1999

A new algorithm for measuring 3-D velocity components of high speed flows were developed using a digital image processing technique. The measuring system consists of three CCD cameras an optical instrument called AOM a digital image grabber and a host computer. The images of mov-ing particles arranged spatially on a rotation plate are taken by two or three CCD cameras and are recorderd onto the image grabber or a video tape recoder. The three-dimensionl velocity com-ponents of the particles are automatically obtained by the developed algorithm In order to verify the validity of this technique three-dimensional velocity data sets obtained from a computer simu-lation of a backward facing step flow were used as test data for the algorithm. an uncertainty analysis associated with the present algorithm is systematically evaluated, The present technique is proved to be used as a tookl for the measurement of unsteady three-dimensional fluid flows.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.559-564
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• 2002

This paper describes a new algorithm named as ray following algorithm which is applied for high-resolution satellite image simulation. The problems of the conventional ray tracing algorithm are pointed out especially when terrain elevations vary abruptly. The proposed algorithm follows the directional ray vector sequentially and thoroughly in order to determine the crossing point of the ray with the terrain surface. This way of sequential height comparison method is regarded as the only way to obtain accurate surface cross-section when a highly variant digital surface model is used. The experimental results show and compare the validities of the conventional and proposed algorithms.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1108-1118
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• 2019

Non-local means (NLM) algorithm is an effective and successful denoising method, but it is computationally heavy. To deal with this obstacle, we propose a novel NLM algorithm with fuzzy metric (FM-NLM) for image denoising in this paper. A new feature metric of visual features with fuzzy metric is utilized to measure the similarity between image pixels in the presence of Gaussian noise. Similarity measures of luminance and structure information are calculated using a fuzzy metric. A smooth kernel is constructed with the proposed fuzzy metric instead of the Gaussian weighted L2 norm kernel. The fuzzy metric and smooth kernel computationally simplify the NLM algorithm and avoid the filter parameters. Meanwhile, the proposed FM-NLM using visual structure preferably preserves the original undistorted image structures. The performance of the improved method is visually and quantitatively comparable with or better than that of the current state-of-the-art NLM-based denoising algorithms.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.2
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• pp.35-47
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• 2018

The 4th industrial revolution, digital image technology has developed beyond the limit of multimedia industry to advanced IT fusion and composite industry. Particularly, application technology related to HCI element algorithm in 3D image object recognition field is actively developed. 3D image object recognition technology evolved into intelligent image sensing and recognition technology through 3D modeling. In particular, image recognition technology has been actively studied in image processing using object recognition recognition processing, face recognition, object recognition, and 3D object recognition. In this paper, we propose a research method of human factor 3D image recognition technology applying human factor algorithm for 3D object recognition. 1. Methods of 3D object recognition using 3D modeling, image system analysis, design and human cognitive technology analysis 2. We propose a 3D object recognition parameter estimation method using FACS algorithm and optimal object recognition measurement method. In this paper, we propose a method to effectively evaluate psychological research techniques using 3D image objects. We studied the 3D 3D recognition and applied the result to the object recognition element to extract and study the characteristic points of the recognition technology.

• International Journal of Automotive Technology
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• v.7 no.2
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• pp.227-235
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• 2006

In this paper a robust image processing method with modified Otsu algorithm to recognize the road lane for a real-time controlled autonomous vehicle is presented. The main objective of a proposed method is to drive an autonomous vehicle safely irrespective of road image qualities. For the steering of real-time controlled autonomous vehicle, a detection area is predefined by lane segment, with previously obtained frame data, and the edges are detected on the basis of a lane width. For stable as well as psudo-robust autonomous driving with "good", "shady" or even "bad" road profiles, the variable threshold with modified Otsu algorithm in the image histogram, is utilized to obtain a binary image from each frame. Also Hough transform is utilized to extract the lane segment. Whether the image is "good", "shady" or "bad", always robust and reliable edges are obtained from the algorithms applied in this paper in a real-time basis. For verifying the adaptability of the proposed algorithm, a miniature vehicle with a camera is constructed and tested with various road conditions. Also, various highway road images are analyzed with proposed algorithm to prove its usefulness.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.5
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• pp.1225-1233
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• 2008

In this paper, the 2D/3D converting algorithm is proposed. The single frame of 2D image is used fur the real-time processing of the proposed algorithm. The proposed algorithm creates a 3D image with the depth map by using the vertical position information of a object in a single frame. In order to real-time processing and improve the hardware complexity, it performs the generation of a depth map using the image sampling, the object segmentation with the luminance standardization and the boundary scan. It might be suitable to a still image and a moving image, and it can provide a good 3D effect on a image such as a long distance image, a landscape, or a panorama photo because it uses a vertical position information. The proposed algorithm can adapt a 3D effect to a image without the restrictions of the direction, velocity or scene change of an object. It has been evaluated with the visual test and the comparing to the MTD(Modified Time Difference) method using the APD(Absolute Parallax Difference).

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.1113-1118
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• 2002

In recognition system of the car license plate, the most important is to extract the image of the license plate from a car image. In this paper, we use ACL (Adaptive Color Luminance) algorithm to extract the license plate image from a car image. The ACL algorithm that uses color and luminance information of a car image is used to extract the image of the license plate. In this paper, color, luminance and other related information of a car image are used to extract the image of the license plate from that of a car. In this reason, we call it the ACL algorithm. The ACL algorithm uses color, luminance information and other related information of a license plate. These informations are avaliable to exact the image of the license plate. The rate of extracting the image of the license plate from a car is 97%. The experimental result of the ACL algorithm for the character region is 92%.

• Journal of Broadcast Engineering
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• v.10 no.2
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• pp.238-246
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• 2005

This paper proposes an iterative high-resolution image interpolation algorithm using spatially adaptive constraints and regularization functional. The proposed algorithm adapts adaptive constraints according to the direction of..edges in an image, and can restore high-resolution image by optimizing regularization functional at each iteration, which is suitable for edge directional regularization. The proposed algorithm outperforms the conventional adaptive interpolation methods as well as non-adaptive ones, which not only can restore high frequency components, but also effectively reduce undesirable effects such as noise. Finally, in order to evaluate the performance of the proposed algorithm, various experiments are performed so that the proposed algorithm can provide good results in the sense of subjective and objective views.