• 제목/요약/키워드: Complex image method

검색결과 724건 처리시간 0.031초

복잡한 영상신호에서 디스터번스 맵을 이용한 움직이는 물체 자동감지, 획득 및 추적 (Automatic Moving Target Detection, Acquisition and Tracking using Disturbance Map in Complex Image Sequences)

  • 조재수;추길환
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
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    • pp.199-202
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    • 2003
  • An effective method is proposed for detecting, acquisition and tracking of a moving object using a disturbance map method in complex image sequences. A significant moving object is detected and tracked within the field of view by computing a modified disturbance map method between an Input image and a temporal average image. This method is very efficient in the serveillance application of digital CCTV and an automatic tracking camera. Experimental results using a real image sequence confirmed that the proposed method can effectively detect and track a significant moving object in complex image sequences.

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Interactive Semantic Image Retrieval

  • Patil, Pushpa B.;Kokare, Manesh B.
    • Journal of Information Processing Systems
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    • 제9권3호
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    • pp.349-364
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    • 2013
  • The big challenge in current content-based image retrieval systems is to reduce the semantic gap between the low level-features and high-level concepts. In this paper, we have proposed a novel framework for efficient image retrieval to improve the retrieval results significantly as a means to addressing this problem. In our proposed method, we first extracted a strong set of image features by using the dual-tree rotated complex wavelet filters (DT-RCWF) and dual tree-complex wavelet transform (DT-CWT) jointly, which obtains features in 12 different directions. Second, we presented a relevance feedback (RF) framework for efficient image retrieval by employing a support vector machine (SVM), which learns the semantic relationship among images using the knowledge, based on the user interaction. Extensive experiments show that there is a significant improvement in retrieval performance with the proposed method using SVMRF compared with the retrieval performance without RF. The proposed method improves retrieval performance from 78.5% to 92.29% on the texture database in terms of retrieval accuracy and from 57.20% to 94.2% on the Corel image database, in terms of precision in a much lower number of iterations.

A Novel Image Dehazing Algorithm Based on Dual-tree Complex Wavelet Transform

  • Huang, Changxin;Li, Wei;Han, Songchen;Liang, Binbin;Cheng, Peng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권10호
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    • pp.5039-5055
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    • 2018
  • The quality of natural outdoor images captured by visible camera sensors is usually degraded by the haze present in the atmosphere. In this paper, a fast image dehazing method based on visible image and near-infrared fusion is proposed. In the proposed method, a visible and a near-infrared (NIR) image of the same scene is fused based on the dual-tree complex wavelet transform (DT-CWT) to generate a dehazed color image. The color of the fusion image is regulated through haze concentration estimated by dark channel prior (DCP). The experiment results demonstrate that the proposed method outperforms the conventional dehazing methods and effectively solves the color distortion problem in the dehazing process.

Optimization-based Image Watermarking Algorithm Using a Maximum-Likelihood Decoding Scheme in the Complex Wavelet Domain

  • Liu, Jinhua;Rao, Yunbo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권1호
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    • pp.452-472
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    • 2019
  • Most existing wavelet-based multiplicative watermarking methods are affected by geometric attacks to a certain extent. A serious limitation of wavelet-based multiplicative watermarking is its sensitivity to rotation, scaling, and translation. In this study, we propose an image watermarking method by using dual-tree complex wavelet transform with a multi-objective optimization approach. We embed the watermark information into an image region with a high entropy value via a multiplicative strategy. The major contribution of this work is that the trade-off between imperceptibility and robustness is simply solved by using the multi-objective optimization approach, which applies the watermark error probability and an image quality metric to establish a multi-objective optimization function. In this manner, the optimal embedding factor obtained by solving the multi-objective function effectively controls watermark strength. For watermark decoding, we adopt a maximum likelihood decision criterion. Finally, we evaluate the performance of the proposed method by conducting simulations on benchmark test images. Experiment results demonstrate the imperceptibility of the proposed method and its robustness against various attacks, including additive white Gaussian noise, JPEG compression, scaling, rotation, and combined attacks.

Improvement of reconstructed image from computer generated psuedo holograms using iterative method

  • Sakanaka, Kouta;Tanaka, Kenichi
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2009년도 IWAIT
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    • pp.578-582
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    • 2009
  • Computer-Generated Hologram (CGH) is generally made by Fourier Transform. CGH is made by an optical reconstruction. Computer-Generated Pseudo Hologram (CGPH) is made up Complex Hadamard Transform instead of CGH which is made by the Fourier Transform. CGPH differs from CGH in point of view the possibility of optical reconstruction. There is an advantage that it cannot be optical reconstruction, in other word, physical leakage of the confidential information is impossible. In this paper, a binary image was converted in Complex Hadamard Transform, and CGPH was made. Improvement of the reconstructed image from CGPH is done by error diffusion method and iterative method. The result that the reconstructed image is improved is shown.

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국내 걸그룹 교복이미지 패션에 나타난 롤리타 콤플렉스(Lolita Complex) (Study on the Lolita Complex of Korea Girl Group's School look image Fashion)

  • 신파람;이효진
    • 한국의류산업학회지
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    • 제19권4호
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    • pp.365-372
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    • 2017
  • This study systematically identified the influence of the school look fashion image on public culture, which is used for increasingly sexualized marketing appeal by domestic Girl Groups. We examined and analyzed the school look fashion image of Girl Groups, focusing on the Lolita complex which is particularly influential in the sexual appeal of domestic popular fashion. The method of this study is based on a literature review from the years 2007 to 2016, when the female girl groups began to receive attention. The music videos of the female girl groups in the top 100 charts of 'Melon' from 2006 to 2-16, which provides the largest mobile music service in Korea, were watched and analyzed as primary data. As a result, it was found that the 'school fashion look image' of adolescence which was used as costumes for Girl Groups, plays a role in commercializing the image of a 'girl', and the types and characteristics of school look fashion image are drawn in two ways. First, it is the image of a seductive Lolita complex. This is the case where young girls wear school look fashion image to emphasize their sexual maturity. Second, it is the case that is using the school look fashion image in order to perform with the 'young girl' concept, as an image of the enchanting Lolita complex; in addition, the erotic body image is more explicitly exposed through choreography and nakedness.

분할된 영상에서의 칼라 코렐로그램을 이용한 영상검색 (Image Retrieval Using Color Correlogram from a Segmented Image)

  • 안명석;조석제
    • 융합신호처리학회 학술대회논문집
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    • 한국신호처리시스템학회 2000년도 추계종합학술대회논문집
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    • pp.153-156
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    • 2000
  • Recently, there has been studied on feature extraction method for efficient content-based image retrieval. Especially, Many researchers have been studying on extracting feature from color Information, because of its advantages. This paper proposes a feature and its extraction method based on color correlogram that is extracted from color information in an image. the proposed method is computed from the image segmented into two parts; the complex part and the plain part. Our experiments show that the performance of the proposed method is better as compared with that of the original color correlogram method.

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Sharing a Large Secret Image Using Meaningful Shadows Based on VQ and Inpainting

  • Wang, Zhi-Hui;Chen, Kuo-Nan;Chang, Chin-Chen;Qin, Chuan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권12호
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    • pp.5170-5188
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    • 2015
  • This paper proposes a novel progressive secret image-hiding scheme based on the inpainting technique, the vector quantization technique (VQ) and the exploiting modification direction (EMD) technique. The proposed scheme first divides the secret image into non-overlapping blocks and categorizes the blocks into two groups: complex and smooth. The blocks in the complex group are compressed by VQ with PCA sorted codebook to obtain the VQ index table. Instead of embedding the original secret image, the proposed method progressively embeds the VQ index table into the cover images by using the EMD technique. After the receiver recovers the complex parts of the secret image by decoding the VQ index table from the shadow images, the smooth parts can be reconstructed by using the inpainting technique based on the content of the complex parts. The experimental results demonstrate that the proposed scheme not only has the advantage of progressive data hiding, which involves more shadow images joining to recover the secret image so as to produce a higher quality steganography image, but also can achieve high hiding capacity with acceptable recovered image quality.

DEFECT INSPECTION IN SEMICONDUCTOR IMAGES USING HISTOGRAM FITTING AND NEURAL NETWORKS

  • JINKYU, YU;SONGHEE, HAN;CHANG-OCK, LEE
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제26권4호
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    • pp.263-279
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    • 2022
  • This paper presents an automatic inspection of defects in semiconductor images. We devise a statistical method to find defects on homogeneous background from the observation that it has a log-normal distribution. If computer aided design (CAD) data is available, we use it to construct a signed distance function (SDF) and change the pixel values so that the average of pixel values along the level curve of the SDF is zero, so that the image has a homogeneous background. In the absence of CAD data, we devise a hybrid method consisting of a model-based algorithm and two neural networks. The model-based algorithm uses the first right singular vector to determine whether the image has a linear or complex structure. For an image with a linear structure, we remove the structure using the rank 1 approximation so that it has a homogeneous background. An image with a complex structure is inspected by two neural networks. We provide results of numerical experiments for the proposed methods.

Formulation of the Green's Functions for Coplanar Waveguide Microwave Devices as Genetic Algorithm-Based Complex Images

  • Han, DaJung;Lee, ChangHyeong;Kahng, Sungtek
    • Journal of Electrical Engineering and Technology
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    • 제12권4호
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    • pp.1600-1604
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    • 2017
  • A new Complex Image Method based on Genetic Algorithm (GA) is proposed to calculate the Green's functions of CPW (coplanar waveguide)-type microwave components and antennas. The closed-forms of the spectral-domain integrals are obtained by the GA, avoiding the conventional procedures of the tedious linear algebra and the sampling conditions sensitive to the complex-variable sampling paths adopted in the Prony's and GPOF methods. The proposed method is compared with the numerical Sommerfeld Integral, which results in good agreement.