• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.312-322
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• 2012

The paper presents an approach for recognizing the broken area of the traffic signs. The method is based on the Recognition System for Traffic Signs (RSTS). This paper describes an approach to using the location histogram matching for the broken traffic signs recognition, after the general process of the image detection and image categorization. The recognition proceeds by using the SIFT matching to adjust the acquired image to a standard position, then the histogram bin will be compared preprocessed image with reference image, and finally output the location and percents value of the broken area. And between the processing, some preprocessing like the blurring is added in the paper to improve the performance. And after the reorganization, the program can operate with the GPS for traffic signs maintenance. Experimental results verified that our scheme have a relatively high recognition rate and a good performance in general situation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.281-287
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• 2010

This study compares transformation algorithms for co-registration of terrestrial laser scan data. Pair-wise transformation which is used for transformation of scan data from more than two different view accumulates errors. ICP algorithm commonly used for co-registration between scan data needs initial geometry information. And it is difficult to co-register simultaneously because of too many control points when managing scan at the same time. Therefore, this study perform global registration technique using matching points. Matching points are extracted automatically from intensity image by SIFT and global registration is performed using GP analysis. There are advantages for operation speed, accuracy, automation in suggested global registration algorithm. Through the result from it, registration algorithms can be developed by considering accuracy and speed.

• Journal of Korea Multimedia Society
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• v.14 no.2
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• pp.201-209
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• 2011

This paper suggests a panorama image stitching system which consists of an image matching algorithm: modified SURF (Speeded Up Robust Feature) and an image blending algorithm: multi-band blending. In this paper, first, Modified SURF is described and SURF is compared with SIFT (Scale Invariant Feature Transform), which also gives the reason why modified SURF is chosen instead of SIFT. Then, multi-band blending is described, Lastly, the structure of a panorama image stitching system is suggested and evaluated by experiments, which includes stitching quality test and time cost experiment. According to the experiments, the proposed system can make the stitching seam invisible and get a perfect panorama for large image data, In addition, it is faster than the sift based stitching system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.561-563
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• 2019

This paper proposes a watermarking method for copyright protection of images used in VR. The Embedding method is that finds the point through the SIFT feature points, inserts the watermark by using DWT and QIM on the surrounding area. The objective image to extract the embedded watermark is the projected image and its method finds the SIFT feature points and extracts watermark data from its surrounding areas after correction by using inverse process of matching and projection in the VR image production process. By comparing the NCC and BER between the extracted watermark and the inserted watermark, the watermark is determined by accumulating the watermark having a threshold value or more. This is confirmed by comparing with a conventional method.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.625-627
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• 2005

Existent distance measurement that use camera is method that use both Stereo Camera and Monocular Camera, There is shortcoming that method that use Stereo Camera is sensitive in effect of a lot of expenses and environment variables, and method that use Monocular Camera are big computational complexity and error. In this study, reduce expense and error using Monocular Camera and I suggest algorithm that measure distance, Extract features using scale Invariant features Transform(SIFT) for distance measurement, and this measures distance through features matching and geometrical analysis, Proposed method proves measuring distance with wall by geometrical analysis free wall through feature point abstraction and matching.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.231-233
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• 2009

The object recognition is one of the major computer vision fields. The object recognition using features(SIFT) is finding common features in input images and query images. But the object recognition using feature methods has suffered of difficulties due to heavy calculations when resizing input images and query images. In this paper, we focused on speed up finding features in the images. we proposed method using block segmentation and histogram. Block segmentation used diving input image and than histogram decided correlation between each 1]lock and query image. This paper has confirmed that tile matching time reduced for object recognition since reducing block.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.1
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• pp.123-128
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• 2018

In this paper, we propose a multi-vehicle object detection algorithm using feature point matching that tracks efficient vehicle objects. The proposed algorithm extracts the feature points of the vehicle using the FAST algorithm for efficient vehicle object tracking. And True if the feature points are included in the image segmented into the 5X5 region. If the feature point is not included, it is processed as False and the corresponding area is blacked to remove unnecessary object information excluding the vehicle object. Then, the post processed area is set as the maximum search window size of the vehicle. And A minimum search window using the outermost feature points of the vehicle is set. By using the set search window, we compensate the disadvantages of the search window size of mean-shift algorithm and track vehicle object. In order to evaluate the performance of the proposed method, SIFT and SURF algorithms are compared and tested. The result is about four times faster than the SIFT algorithm. And it has the advantage of detecting more efficiently than the process of SUFR algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.1025-1034
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• 2009

In steel making production line, steel slabs are given a unique identification number. This identification number, Slab management number(SMN), gives information about the use of the slab. Identification of SMN has been done by humans for several years, but this is expensive and not accurate and it has been a heavy burden on the workers. Consequently, to improve efficiency, automatic recognition system is desirable. Generally, a recognition system consists of text localization, text extraction, character segmentation, and character recognition. For exact SMN identification, all the stage of the recognition system must be successful. In particular, the text localization is great important stage and difficult to process. However, because of many text-like patterns in a complex background and high fuzziness between the slab and background, directly extracting text region is difficult to process. If the slab region including SMN can be detected precisely, text localization algorithm will be able to be developed on the more simple method and the processing time of the overall recognition system will be reduced. This paper describes about the slab region localization using SIFT(Scale Invariant Feature Transform) features in the image. First, SIFT algorithm is applied the captured background and slab image, then features of two images are matched by Nearest Neighbor(NN) algorithm. However, correct matching rate can be low when two images are matched. Thus, to remove incorrect match between the features of two images, geometric locations of the matched two feature points are used. Finally, search rectangle method is performed in correct matching features, and then the top boundary and side boundaries of the slab region are determined. For this processes, we can reduce search region for extraction of SMN from the slab image. Most cases, to extract text region, search region is heuristically fixed [1][2]. However, the proposed algorithm is more analytic than other algorithms, because the search region is not fixed and the slab region is searched in the whole image. Experimental results show that the proposed algorithm has a good performance.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.193-196
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• 2009

여러 개의 영상으로부터 스케일, 조명, 시점 등의 환경변화를 고려하여 대응점을 찾는 일은 쉽지 않다. SURF는 이러한 환경변화에 불변하는 특징점을 찾는 알고리즘중 하나로서 일반적으로 성능이 우수하다고 알려진 SIFT와 견줄만한 성능을 보이면서 속도를 크게 향상시킨 알고리즘이다. 하지만 SURF는 그레이공간 상의 정보만 이용함에 따라 컬러공간상에 주어진 많은 유용한 특징들을 활용하지 못한다. 본 논문에서는 강인한 컬러특정정보를 포함하는 확장된 SURF알고리즘을 제안한다. 제안하는 방법의 우수성은 다양한 조명환경과 시점변화에 따른 영상을 SIFT와 SURF 그리고 제안하는 컬러정보를 적용한 SURF알고리즘과 비교 실험을 통해 입증하였다.

• International Journal of Contents
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• v.13 no.4
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• pp.70-79
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• 2017

Images are an important element in patents and many experts use images to analyze a patent or to check differences between patents. However, there is little research on image analysis for patents partly because image processing is an advanced technology and typically patent images consist of visual parts as well as of text and numbers. This study suggests two methods for using image processing; the Scale Invariant Feature Transform(SIFT) algorithm and Optical Character Recognition(OCR). The first method which works with SIFT uses image feature points. Through feature matching, it can be applied to calculate the similarity between documents containing these images. And in the second method, OCR is used to extract text from the images. By using numbers which are extracted from an image, it is possible to extract the corresponding related text within the text passages. Subsequently, document similarity can be calculated based on the extracted text. Through comparing the suggested methods and an existing method based only on text for calculating the similarity, the feasibility is achieved. Additionally, the correlation between both the similarity measures is low which shows that they capture different aspects of the patent content.