• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.820-822
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• 2003

웨이블릿 변환 영역에 제안한 알고리즘으로 여러 공격에 강인한 워터마크를 삽입하고 성능을 분석하였다. 영상의 저작권 보호를 위해 웨이블릿 변환영역의 LH, HL, HH의 중대역에 128비트열의 워터마크를 삽입하였다. 제안한 방법의 강인성을 실험하기 위해 명도 변화, 콘트라스트 변화, 노이즈, 가우시안 등 과 같은 영상처리를 하였다. 실험결과 화질의 열화를 최소로 하여 워터마크를 삽입하여 높은 효율을 얻었다.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.330-333
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• 2003

본 논문에서는 웨이브릿 변환 영역에 제안한 알고리듬으로 여러 공격에 강인한 워터마크를 삽입하였다. 추출된 워터마크는 정칙화 영상복원에 활용하는 Tikhonov-Miller 처리를 함으로써 워터마크의 유사성 판별을 쉽게 하였다. 제안한 방법의 강인성과 유사성 향상을 실험하기 위해 명암, 크기 변화, 필터링, 잘라내기, 히스토그램 평활화, 손실압축(JPEG, gif)과 같은 영상처리를 하였다. 실험 결과 제안한 방법은 비가시성을 고려한 강인한 워터마크를 삽입할 수 있고 여러 공격에 대해서 더욱 높은 상관 계수로 추출할 수가 있었다.

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2776-2785
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• 1998

An image retrieval system based on image content is a key issue for building and managing large multimedia database, such as art galleries and museums, trademarks and copyrights, and picture archiving and communication system. Therefore, the interest on the subject of content-based image retrieval has been greatly increased for the last few years. This paper proposes a feature-based image retrieval technique which uses a compound feature vector representing both of color and shape of an image. Color information for the feature vector is obtained using the algebraic moment of each pixel of an image based on the property of regional color distribution. Shape information for the feature vector is obtained using the Improved Moment Invariant(IMI) which reduces the quantity of computation and increases retrieval efficiency. In the preprocessing phase for extracting shape feature, we transform a color image into a gray image. Since we make use of the modified DCT algorithm, it is implemented easily and can extract contour in real time. As an experiment, we have compared our method with previous methods using a database consisting of 150 automobile images, and the results of the experiment have shown that our method has the better performance on retrieval effectiveness.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.77-86
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• 2014

Mobile devices are generally using app images which are artificially designed. Accordingly, this paper presents adjusting device brightness based on app image categorization for enhancing the visibility under various light condition. First, the proposed method performed two prior subjective tests under various lighting conditions for selecting features of app images concerning visibility and for selecting satisfactory range of device brightness for each app image. Then, the relationship between selected features of app image and satisfactory range of device brightness is analyzed. Next, app images are categorized by using two features of average brightness of app image and distribution ratio of advanced colors that are related to satisfaction range of device brightness. Then, optimal device brightness for each category is selected by having the maximum frequency of satisfaction device brightness. Experimental results show that the categorized app images with optimal device brightness have high satisfaction ratio under various light conditions.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.295-296
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• 2016

본 연구에서는 LED 광 자극이 뇌의 어느 영역을 자극하여 신경신호를 전달하는지에 관해서 관찰하고자 연구를 진행하였다. 광 자극에 의한 뇌 영역의 활성변화를 관찰하기 위하여 실험용 소동물과 영상장비인 9.4T MRI를 이용하여 연구를 수행 하였다. 실험용 소동물은 Balb/c 마우스를 이용하였으며 기능적 자기공명영상 획득 방법 중 하나인 에코평면영상 기법을 이용하여 뇌 영상을 획득 하였다. 획득한 영상을 바탕으로 뇌 영역의 자극 정도를 확인해보기 위해 영상처리기법인 재편성(realignment), 일치(co-registration), 표준화(normalization), 평활화(smoothing) 방법으로 영상을 전처리 하고, statistical parametric map (SPM12)을 사용하여 분석하였다. 본 연구에서는 광자극이 소동물 뇌 영역 중 하나인 상구(Superior colliculus)영역과 대뇌의 시각피질 (visual cortex, V1) 영역에서 자극을 일으키는 것을 확인할 수 있었다.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.96-96
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• 2017

농산물 수확 이후 저장 유통 과정에서 일어나는 생리적 현상 변화에 따른 내부품질의 측정 분석연구가 활발히 진행되고 있다. 이 연구에서는 비파괴 측정 방법들 중 하나인 자기공명영상(Magnetic Resonance Imaging, MRI) 기술을 활용하여 후숙 과일인 키위의 저장 일수에 따른 형태 및 내부 구조의 변화를 조사하였다. 공시재료는 국내에서 판매되고 있는 키위들 중 3품종(뉴질랜드산 Sun Gold, 뉴질랜드산 Green, 칠레산 Jin Green)별로 균일한 크기의 과일 5개씩을 이용하였으며, 시료를 실험실내($16.6^{\circ}C$, 38% RH)에서 18~19 일간 보관하면서 3~5일 간격으로 5회 시험하였다. 전북대 농업과학기술연구소가 보유하고 있는 MRI(M10, Aspect Imaging, Israel)를 활용하여 영상 이미지를 얻었으며, 저장 기간에 따른 무게 감소는 전자저울(한성, HK-series)을 이용하였다. 자기공명영상 이미지는 Gradient-Eco 펄스열을 사용하였고, 횡단면(Axial)의 영상면(Image-direction)을 중심으로 영상영역(Field of View, FOV)은 $80mm{\times}80mm$로 1회 촬영 할 때 마다 30개의 영상들을 얻었다. 저장 기간이 길어질수록 내부 공동현상이 커지는 것으로 나타났고, 뉴질랜드산 Sun Gold 품종은 다른 두 품종보다 내부 공동이 빠르게 나타났다. 실험이 끝나는 날에는 껍질이 연화되어 타원형의 형체를 계속 유지하지 못하고 붕괴되는 이미지를 MRI를 통해서 관찰 할 수 있었다. 시간이 지남에 따라 영상들의 위치가 일정하지 않고 일부 회전을 한 것처럼 나타났다. 이는 키위 전용 홀더를 만들어 고정하지 않고 측정하다보니 생긴 오차로 생각 되었다. 키위를 건조한 공간에 오래 보관하였기 때문에 시간이 지남에 따라 수분증발과 연화된 껍질 사이로 과육이 흘러 일부를 제외한 대부분의 키위 무게가 일정하게 감소하는 것을 알 수 있었다.

• 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.

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.95-105
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• 2006

This paper proposes a novel approach to represent the image by using shape descriptor having an information of area. The proposed descriptor is a set of vectors, consists of radius, area and direction parameters in the concentrated center point. Due to the area parameter, we know our descriptor can obtain the information of area. Also, we give an extended shape descriptor to get more detailed representation. To do this, we move the center point of our vision to that point for region of interest. By doing so about all of region of interest, we can get our descriptor for detailed information of the image. From more detailed descriptor, it's natural that it's more efficient fur representation, retrievals and so on. We make it the normalized pattern and expand to improve its quality. The proposed method is invariant to scale, position and rotation. The results show that it can be used efficiently for image representation as we can see in retrievals of silhouette images.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.761-769
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• 2012

In this paper, a setting method of initial cluster centers and color image segmentation using superpixels and Fuzzy C-means(FCM) algorithm is proposed. Generally, the FCM can be widely used to segment color images, and an element is assigned to any cluster with each membership values in the FCM. However the algorithm has a problem of local convergence by determining the initial cluster centers. So the selection of initial cluster centers is very important, we proposed an effective method to determine the initial cluster centers using superpixels. The superpixels can be obtained by grouping of some pixels having similar characteristics from original image, and it is projected $La^*b^*$ feature space to obtain the initial cluster centers. The proposed method can be speeded up because number of superpixels are extremely smaller than pixels of original image. To evaluate the proposed method, several color images are used for computer simulation, and we know that the proposed method is superior to the conventional algorithm by the experimental results.

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1115-1127
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• 2010

In order to increase the productivity in manufacturing TFT-LCD(thin film transistor-liquid crystal display), it is essential to classify defects that occur during the production and make an appropriate decision on whether the product with defects is scrapped or not. The decision mainly depends on classifying the defects accurately. In this paper, we present an effective classification method for film defects acquired in the panel production line by analyzing the intensity distribution and shape feature of the defects. We first generate a binary image for each defect by separating defect regions from background (non-defect) regions. Then, we extract various features from the defect regions such as the linearity of the defect, the intensity distribution, and the shape characteristics considering intensity, and construct a referential image database that stores those feature values. Finally, we determine the type of a defect by matching a defect image with a referential image in the database through the matching cost function between the two images. To verify the effectiveness of our method, we conducted a classification experiment using defect images acquired from real TFT-LCD production lines. Experimental results show that our method has achieved highly effective classification enough to be used in the production line.