• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.380-383
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• 2008

본 논문은 단순한 키워드 검색에서 발생하는 오차를 줄이기 위해 이미지의 코너정보와 그레이스케일 히스토그램 정제를 이용한 영상 검색 시스템을 구현하고자 한다. 먼저 원하는 이미지의 특정을 추출하는 단계와 추출된 특징을 분석하는 단계, 확보된 정보를 데이터베이스로부터 검색하는 단계, 그 결과 안에서의 그레이스케일 히스토그램 정제 방법으로 다시 재검색하는 단계, 마지막으로 정확한 정보 추출단계를 거치게 된다. 구현 알고리즘은 검색 단계에 있어서 크게 2단계로 나눠진다. 먼저 이미지를 에지로 변환 코너정보를 추출하는 단계, 코너 점의 픽셀을 3*3으로 나누어 RGB중의 픽셀의 합을 하는 단계, 그 코너 값을 데이터베이스와 비교하는 단계, 최대 500개까지의 추출된 이미지를 데이터베이스에 저장되는 단계로 이루어지며 다음 단계는 원 이미지를 그레이스케일로 변환 등질화하는 단계, 히스토그램 정보 획득하는 단계, 8*8 개의 빈으로 나누어 최대 색상정보 값을 추출하는 단계, 그리고 최대 색상정보 영역을 1단계 결과 값과 비교하여 정확한 검색을 얻는 단계로 구성되며 시뮬레이션 결과는 우수한 정확도를 보여 주고 있다.

• Korean Journal of Optics and Photonics
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• v.13 no.2
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• pp.117-122
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• 2002

Some 10$\times$10 micro-lens arrays of a period of 300 ${\mu}{\textrm}{m}$, a thickness of 17 ${\mu}{\textrm}{m}$, and a focal length of 2.2 mm are fabricated by exposing a thick layer of photoresist through a grayscale mask via UV proximity printing. The grayscale mask is fabricated in a holographic film by reducing (6.6X) a high-resolution black-and-white film where a grayscale patters of a micro-lens array designed by a computer has been written using a film recorder. The proposed method has the advantage of a low fabrication cost, a fill-factor of almost 100% and the ease of realizing an aspheric lens.

• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.41-46
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• 2021

The method of the edge detection algorithm based on grayscale mathematical morphology has the advantage that image noise can be removed and processed in parallel, and the operation speed is fast. However, the method of detecting the edge of an image using a single structural scale element may be affected by image information. The characteristics of grayscale morphology may be limited to the edge information result of the operation result by repeatedly performing expansion, erosion, opening, and containment operations by repeating structural elements. In this paper, we propose an edge detection algorithm that applies a structural element with strong directionality to noise and then applies weighted entropy to each pixel information in the element. The result of applying the multi-scale structural element applied to the image and the result of applying the directional weighted entropy were compared and analyzed, and the simulation result showed that the proposed algorithm is superior in edge detection.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.11-20
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• 2015

Digital watermarking provides electronic means for proving the copyrights of distributed digital media copies. Research on digital watermarking for images is recently directed toward that for color images extensively used in real life, based on the substantial results in digital watermarking for gray-scale images. Color images have multiple channels, each of which corresponds to a gray-scale image. While there are some watermarking techniques for color images that just apply those for gray-scale images to one channel of the color images, the correlation characteristics between the channels are not considered in them. This paper proposes a zero-watermarking technique that makes keys via combining an image dependent watermark, created through comparing two channels of the color image and copyright watermark scrambled. Due to zero-watermarking, it does not change anything of cover(host) images. Watermark images are robust against some common attacks such as sharpening, blurring, JPEG lossy compression, scaling, and cropping.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.151-154
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• 2008

In this paper, this program which is Retrieval System using Image Gray-scale histogram and Edge features is used to reduce the errors incurred by inputting methods which are used in a current Retrieval System. The Retrieval Algorithm is proceeding with several steps which are extracting features of images quality, extracting edge features and refining images, analysing extracted features, retaining important information from analyzed features, retrieving retained information from database, extracting and comparing among images from retrieved database. The proposed Retrieval System is used for a fast retrieval with accuracy and it is confirmed through simulations.

• Proceedings of the Optical Society of Korea Conference
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• 2004.02a
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• pp.130-131
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• 2004

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.183-188
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• 2010

In this paper we propose a detection method of the medial axis of the continuous stripes on the LoG scale-space. Our method detects the medial axis of continuous stripes iteratively by varying the scale of LoG operator. Small-scale LoG operator detects two +/- pole pairs centered on the edge positions of stripe by the zero-crossing detection. The more increase the scale of LoG scale-space, the more close two poles to the medial axis of stripe. The medial axis of continuous stripe is the position where two poles is overlapped. The proposed method detected robustly the medial axis of continuous stripes stronger than the thinning methods used to binary image.

• Journal of Korea Multimedia Society
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• v.7 no.2
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• pp.164-172
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• 2004

Halftoning of gray-scale image is a process to produce a binary image. The error diffusion halftoning method produces high qualify binary image but that has some defects such as sharpening and directional artifacts. We propose the threshold modulation to reduce such defects. The proposed algorithm uses thresholds reflecting local characteristic of image. We calculate thresholds which minimize errors of flat region of each gray-scale level by using a linear gain between original image and error-diffused image and then represent edge by compensating thresholds in proportion to edge information. The proposed method improves on halftone quality by minimizing an error which cause sharpening and directional artifact.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.4
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• pp.288-294
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• 2017

Recently, deep learning using convolutional neural network (CNN) has been extensively studied in image recognition. Convolution consists of addition and multiplication. Multiplication is computationally expensive in hardware implementation, relative to addition. It is also important factor limiting a chip design in an embedded deep learning system. In this paper, I propose a parallel-addition processing algorithm that converts grayscale images to the superposition of binary images and performs convolution only with addition. It is confirmed that the convolution can be performed by a parallel-addition method capable of reducing the processing time in experiment for verifying the availability of proposed algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.4
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• pp.656-664
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• 2006

In this paper, we introduce a new LUT based watermarking method for a halftone image. Watermark bits are hidden at pseudo-random locations of halftone image in the proposed method. The pixel values of the halftone image are determined from the LUT entry indexed by both the neighborhood halftone pixels and current grayscale value. The LUT is trained by a set of grayscale images and corresponding halftone images. Advantage of the LUT method is that it can be executed very fast compared with other watermarking methods for a halftone image. Therefore, the algorithm can be embedded in a printer. Experiments for real scanned images showed that the method is a feasible method to hide the large amount of data within a halftone image without noticeable distortion and comparing to the DHED method, is almost same in quality but significantly shorten in processing time.