• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.273-273
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• 2000

We present a new scheme to increase the performance of edge-preserving image smoothing from the parameter tuning of a Markov random field (MRF) function. The method is based on automatic control of the image smoothing-strength in MRF model ing in which an introduced parameter function is based on control of enforcing power of a discontinuity-adaptive Markov function and edge magnitude resulted from discontinuities of image intensity. Without any binary decision for the edge magnitude, adaptive control of the enforcing power with the full edge magnitude could improve the performance of discontinuity-preserving image smoothing.

• 한국멀티미디어학회논문지
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• 제18권7호
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• pp.827-833
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• 2015

In this paper, we have compared three level set-based active contour (LSAC) methods on inhomogeneous MR image segmentation which is known as an important role of brain diseases to diagnosis and treatment in early. MR image is often occurred a problem with similar intensities and weak boundaries which have been causing many segmentation methods. However, LSAC method could be able to segment the targets such as the level set based on the local image fitting energy, the local binary fitting energy, and local Gaussian distribution fitting energy. Our implemented and tested the subcortical image segmentations were the corpus callosum and hippocampus and finally demonstrated their effectiveness. Consequently, the level set based on local Gaussian distribution fitting energy has obtained the best model to accurate and robust for the subcortical image segmentation.

• 정보통신설비학회논문지
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• 제9권2호
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• pp.73-79
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• 2010

The most popular technique for image retrieval in a heterogeneous collection of color images is the comparison of images based on their color histogram. The color histogram describes the distribution of colors in the color space of a color image. In the most image retrieval systems, the color histogram is used to compute similarities between the query image and all the images in a database. But, small changes in the resolution, scaling, and illumination may cause important modifications of the color histogram, and so two color images may be considered to be very different from each other even though they have completely related semantics. A new method of color feature representation based on the 3-dimensional RGB color map is proposed to improve the defects of the color histogram. The proposed method is based on the three 2-dimensional projection map evaluated by projecting the RGB color space on the RG, GB, and BR surfaces. The experimental results reveal that the proposed is less sensitive to small changes in the scene and that achieve higher retrieval performances than the traditional color histogram.

• Journal of information and communication convergence engineering
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• 제2권2호
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• pp.123-127
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• 2004

The most popular technique for image retrieval in a heterogeneous collection of color images is the comparison of images based on their color histogram. The color histogram describes the distribution of colors in the color space of a color image. In the most image retrieval systems, the color histogram is used to compute similarities between the query image and all the images in a database. But, small changes in the resolution, scaling, and illumination may cause important modifications of the color histogram, and so two color images may be considered to be very different from each other even though they have completely related semantics. A new method of color feature representation based on the 3-dimensional RGB color map is proposed to improve the defects of the color histogram. The proposed method is based on the three 2-dimensional projection map evaluated by projecting the RGB color space on the RG, GB, and BR surfaces. The experimental results reveal that the proposed is less sensitive to small changes in the scene and that achieve higher retrieval performances than the traditional color histogram.

• 한국멀티미디어학회논문지
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• 제25권9호
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• pp.1291-1306
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• 2022

The dual image-based reversible data hiding scheme embeds secret data into two images to increase the embedding capacity of secret data. The dual image-based reversible data hiding scheme can transmit a lot of secret data. Therefore, various schemes have been proposed until recently. In 2021, Chen and Hong proposed a dual image-based reversible data hiding scheme that embeds a large amount of secret data using a reference matrix, secret data, and bit values. However, in this paper, more secret data can be embedded than Chen and Hong's scheme. To achieve this goal, the proposed scheme generates polynomials and shared values using secret sharing scheme, and embeds secret data using reference matrix and septenary number, and random value. Experimental results show that the proposed scheme can transmit more secret data to the receiver while maintaining the image quality similar to other dual image-based reversible data hiding schemes.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2022년도 하계학술대회
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• pp.825-828
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• 2022

In this paper, we propose an efficient image size selection method for video-based point cloud compression. The current MPEG video-based point cloud compression reference encoding process configures a threshold on the size of images while converting point cloud data into images. Because the converted image is compressed and restored by the legacy video codec, the size of the image is one of the main components in influencing the compression efficiency. If the image size can be made smaller than the image size determined by the threshold, compression efficiency can be improved. Here, we studied how to improve the compression efficiency by selecting the best-fit image size generated during video-based point cloud compression. Experimental results show that the proposed method can reduce the encoding time by 6 percent without loss of coding performance compared to the test model 15.0 version of video-based point cloud encoder.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.450-453
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• 2002

In this paper a Phase-based virtual image encryption and decryption techniques based on a joint transform correlator (JTC) are proposed. In this method, an encrypted image is obtained by multiplying a phase-encoded virtual image that contains no information from the decrypted image with a random phase. Even if this encryption process converts a virtual image into a white-noise-like image, the unauthorized users can permit a counterfeiting of the encrypted image by analyzing the random phase mask using some phase-contrast technique. However, they cannot reconstruct the required image because the virtual image protects the original image from counterfeiting and unauthorized access. The proposed encryption technique does not suffer from strong auto-correlation terms appearing in the output plane. In addition, the reconstructed data can be directly transmitted to a digital system for real-time processing. Based on computer simulations, the proposed encryption technique and decoding system were demonstrated as adequate for optical security applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권7호
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• pp.3620-3637
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• 2019

Since the birth of Synthetic Aperture Radar (SAR), it has been widely used in the military field and so on. However, the existence of speckle noise makes a good deal inconvenience for the subsequent image processing. The continuous development of sparse representation (SR) opens a new field for the speckle suppressing of SAR image. Although the SR de-noising may be effective, the over-smooth phenomenon still has bad influence on the integrity of the image information. In this paper, one novel SAR image de-noising method based on residual image fusion and sparse representation is proposed. Firstly we can get the similar block groups by the non-local similar block matching method (NLS-BM). Then SR de-noising based on the adaptive K-means singular value decomposition (K-SVD) is adopted to obtain the initial de-noised image and residual image. The residual image is processed by Shearlet transform (ST), and the corresponding de-noising methods are applied on it. Finally, in ST domain the low-frequency and high-frequency components of the initial de-noised and residual image are fused respectively by relevant fusion rules. The final de-noised image can be recovered by inverse ST. Experimental results show the proposed method can not only suppress the speckle effectively, but also save more details and other useful information of the original SAR image, which could provide more authentic and credible records for the follow-up image processing.

• 한국통신학회논문지
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• 제32권10C호
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• pp.990-999
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• 2007

본 논문에서는 효과적인 영상 검색을 위한 방법으로서 JSEG 영상 분할 기법을 통한 영역 기반의 영상 인덱싱 및 검색 기법을 제안한다. JSEG은 영상을 색상 분류에 따라 양자화하고 이에 영역 윈도우를 적용시켜 J-image를 만든 다음, 세부 분할된 영역의 성장과 병합을 통하여 영상을 효과적으로 분할하는 방법이다. 제안하는 영상 검색 시스템은 JSEG에 의해 분할된 영상을 사용자에게 질의 영상으로 주고, 사용자로 하여금 분할 영상에서 관심 영역군(群)을 선택하게 한다. 그리고 나서, 사용자 질의에 의해 선택된 영역의 MBR을 구하고 이 영역의 중심을 기준으로 다중 윈도우 마스크를 생성하여 적용시킴으로써 특정 관심 영역을 중심으로 한 영상의 전역적인 특징을 추출한다. 최종적으로 추출된 특징의 성능 비교를 위한 기술자로는 누적 히스토그램을 이용하였다. 제안된 방법은 특정 영역에서의 특징과 전역 특징을 동시에 추출하여 검색에 이용함으로써 보다 빠르고 정확하게 사용자가 원하는 영상을 제공할 수 있다. 실험 결과는 영상 색인 및 검색에 있어서 제안된 방법이 영상 기반의 검색 기법과 비교하여 더 효과적임을 보여준다.

• 제어로봇시스템학회논문지
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• 제14권5호
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• pp.473-482
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• 2008

In this paper we propose an expert system for content-based image retrieval with object database. The proposed system finds keyword by using knowledge-base and feature of extracted object, and retrieves image by using keyword based image retrieval method. The system can decrease error of image retrieval and save running time. The system also checks whether similar objects exist or not. If not, user can store information of object in object database. Proposed system is flexible and extensible, enabling experts to incrementally add more knowledge and information. Experimental results show that the proposed system is more effective than existing content-based image retrieval method in running time and precision.