• Title/Summary/Keyword: weighted histogram

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Blind Quality Metric via Measurement of Contrast, Texture, and Colour in Night-Time Scenario

  • Xiao, Shuyan;Tao, Weige;Wang, Yu;Jiang, Ye;Qian, Minqian.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.11
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    • pp.4043-4064
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    • 2021
  • Night-time image quality evaluation is an urgent requirement in visual inspection. The lighting environment of night-time results in low brightness, low contrast, loss of detailed information, and colour dissonance of image, which remains a daunting task of delicately evaluating the image quality at night. A new blind quality assessment metric is presented for realistic night-time scenario through a comprehensive consideration of contrast, texture, and colour in this article. To be specific, image blocks' color-gray-difference (CGD) histogram that represents contrast features is computed at first. Next, texture features that are measured by the mean subtracted contrast normalized (MSCN)-weighted local binary pattern (LBP) histogram are calculated. Then statistical features in Lαβ colour space are detected. Finally, the quality prediction model is conducted by the support vector regression (SVR) based on extracted contrast, texture, and colour features. Experiments conducted on NNID, CCRIQ, LIVE-CH, and CID2013 databases indicate that the proposed metric is superior to the compared BIQA metrics.

An Improved LBP-based Facial Expression Recognition through Optimization of Block Weights (블록가중치의 최적화를 통해 개선된 LBP기반의 표정인식)

  • Park, Seong-Chun;Koo, Ja-Young
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.11
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    • pp.73-79
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    • 2009
  • In this paper, a method is proposed that enhances the performance of the facial expression recognition using template matching of Local Binary Pattern(LBP) histogram. In this method, the face image is segmented into blocks, and the LBP histogram is constructed to be used as the feature of the block. Block dissimilarity is calculated between a block of input image and the corresponding block of the model image. Image dissimilarity is defined as the weighted sum of the block dissimilarities. In conventional methods, the block weights are assigned by intuition. In this paper a new method is proposed that optimizes the weights from training samples. An experiment shows the recognition rate is enhanced by the proposed method.

Bit-Rate Control Using Histogram Based Rate-Distortion Characteristics (히스토그램 기반의 비트율-왜곡 특성을 이용한 비트율 제어)

  • 홍성훈;유상조;박수열;김성대
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.9B
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    • pp.1742-1754
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    • 1999
  • In this paper, we propose a rate control scheme, using histogram based rate-distortion (R-D) estimation, which produces a consistent picture quality between consecutive frames. The histogram based R-D estimation used in our rate control scheme offers a closed-form mathematical model that enable us to predict the bits and the distortion generated from an encoded frame at a given quantization parameter (QP) and vice versa. The most attractive feature of the R-D estimation is low complexity of computing the R-D data because its major operation is just to obtain a histogram or weighted histogram of DCT coefficients from an input picture. Furthermore, it is accurate enough to be applied to the practical video coding. Therefore, the proposed rate control scheme using this R-D estimation model is appropriate for the applications requiring low delay and low complexity, and controls the output bit-rate ad quality accurately. Our rate control scheme ensures that the video buffer do not underflow and overflow by satisfying the buffer constraint and, additionally, prevents quality difference between consecutive frames from exceeding certain level by adopting the distortion constraint. In addition, a consistent considering the maximum tolerance BER of the voice service. Also in Rician fading channel of K=6 and K=10, considering CLP=$10^{-3}$ as a criterion, it is observed that the performance improment of about 3.5 dB and 1.5 dB is obtained, respectively, in terms of $E_b$/$N_o$ by employing the concatenated FEC code with pilot symbols.

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A Study on Multiple Filter for Mixed Noise Removal (복합잡음 제거를 위한 다중 필터에 관한 연구)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.11
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    • pp.2029-2036
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    • 2017
  • Currently, the demand for multimedia services is increasing with the rapid development of the digital age. Image data is corrupted by various noises and typical noise is mainly AWGN, salt and pepper noise and the complex noise that these two noises are mixed. Therefore, in this paper, the noise is processed by classifying AWGN and salt and pepper noise through noise judgment. In the case of AWGN, the outputs of spatial weighted filter and pixel change weighted filter are composed and processed, and the composite weights are applied differently according to the standard deviation of the local mask. In the case of salt and pepper noise, cubic spline interpolation and local histogram weighted filters are composed and processed. This study suggested the multiple image restoration filter algorithm which is processed by applying different composite weights according to the salt and pepper noise density of the local mask.

Local Linear Transform and New Features of Histogram Characteristic Functions for Steganalysis of Least Significant Bit Matching Steganography

  • Zheng, Ergong;Ping, Xijian;Zhang, Tao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.4
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    • pp.840-855
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    • 2011
  • In the context of additive noise steganography model, we propose a method to detect least significant bit (LSB) matching steganography in grayscale images. Images are decomposed into detail sub-bands with local linear transform (LLT) masks which are sensitive to embedding. Novel normalized characteristic function features weighted by a bank of band-pass filters are extracted from the detail sub-bands. A suboptimal feature set is searched by using a threshold selection algorithm. Extensive experiments are performed on four diverse uncompressed image databases. In comparison with other well-known feature sets, the proposed feature set performs the best under most circumstances.

An Evaluation of Image Retrieval used Weighted Color Histogram (가중치 칼라 히스토그램을 통한 이미지 검색의 성능평가)

  • Lee, Yong-Hwan;Lee, Yu-Kyong;Lee, June-Hwan;Rhee, Sang-Burm;Kim, Young-Seop
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.397-398
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    • 2006
  • 본 논문에서는 이미지 검색을 위해 가장 기본적인 요소인 이미지 색상에 따른 칼라 분포정보를 이용하고 다양한 요소에 따라 가중치를 부여한 칼라기반의 검색 기술자를 제안하였고 실험적 평가를 통하여 제안 기술자의 성능을 평가하였다. 칼라 히스토그램을 통한 이미지 검색 기술자를 설계하는데 있어 칼라모델은 HSV, 웨이블릿 변환 필터는 D9/7, 웨이블릿 분해는 2 레벨을 적용하였을 때 가장 좋은 검색효율성을 보였다.

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Efficient Contrast Enhancement Using an Adaptive Weighted Kernel based on 2-D Histogram (2차원 히스토그램 기반 적응적 가중치 커널을 이용한 효율적 대비 강화)

  • Wee, Kyungchul;Kim, Changick
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2016.11a
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    • pp.85-88
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    • 2016
  • 대비 강화는 컴퓨터 비젼, 영상 처리, 패턴인식에서 전처리 과정으로 이용되며 그 역할이 중요하다. 2차원 히스토그램을 이용한 대비 강화 방법은 인접 픽셀 간의 정보를 이용해 대비를 강화시키기 때문에 1차원 히스토그램을 이용한 대비 강화 방법보다 우수하다. 2차원 히스토그램 기반 알고리즘에서 2차원 히스토그램의 인접픽셀 간의 화소값 차이에 따라 가중치를 주는 커널 (kernel)이 사용된다. 이러한 커널은 영상 마다 같은 가중치를 곱해주기 때문에 원하는 대비를 시켜주지 못하는 단점이 있다. 이에 본 논문은 2차원 히스토그램을 1차원 히스토그램으로 정사영을 시켜 평균값과 표준편차를 통해 2차원 히스토그램을 통계학적으로 분석한다. 그리고 선형회귀법을 이용하여 2차원 히스토그램의 통계적 정보에 따른 적응적 가중치 커널을 제안하고, 이를 이용하여 효율적 대비 강화를 한다. 실험 결과를 통해 제안하는 방법이 기존의 알고리즘에 비해 대비 향상 성능이 더 우수한 방법임을 확인하였다.

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Content-based Image Retrieval using Weighted Color Histogram and Spatial Distribution of Dominant Colors (가중 색 히스토그램과 지배적인 색의 영상 공간 분포를 이용한 내용기반 영상 검색)

  • Park, Du-Sik;Han, Jun-Hui
    • Journal of KIISE:Software and Applications
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    • v.28 no.3
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    • pp.285-297
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    • 2001
  • 본 논문에서는 특정한 객체의 색 분포 모델링으로부터 얻어지는 가중 색 히스토그램과 지배적인 색의 영상공간 분포특성을 이용한 내용기반 영상 검색 방법을 제안한다. 특정한 객체의 예로 사람 얼굴을 선택했고, 그것의 색 분포를 u*-v* 색도 공간에서 모델링 했으며, 모델의 정규화된 부피를 균등 양자화된 색도 공간의 각 빈(bin)의 히스토그램 값에 대한 가중치로 결정하고, 결정된 가중치를 히스토그램 정합 과정에 적용하였다. 또한 색 히스토그램 값이 큰 특정한 수의 빈으로 정의되는 지배적인 색의 영상 공간 분포를 가중 색 히스토그램과 함께 유사성의 측정기준으로 사용하였다. 제안한 검색 방법을 500여개의 영상에 대해 실험한 결과 제안한 방법이 얼굴을 포함하는 영상을 질의로 주었을 때 얼굴을 포함하는 영상을 우선적으로 찾는데 효과적임을 확인하였다.

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Accurate PCB Outline Extraction and Corner Detection for High Precision Machine Vision (고정밀 머신 비전을 위한 정확한 PCB 윤곽선과 코너 검출)

  • Ko, Dong-Min;Choi, Kang-Sun
    • Journal of the Semiconductor & Display Technology
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    • v.16 no.3
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    • pp.53-58
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    • 2017
  • Recently, advance in technology have increased the importance of visual inspection in semiconductor inspection areas. In PCB visual inspection, accurate line estimation is critical to the accuracy of the entire process, since it is utilized in preprocessing steps such as calibration and alignment. We propose a line estimation method that is differently weighted for the line candidates using a histogram of gradient information, when the position of the initial approximate corner points is known. Using the obtained line equation of the outline, corner points can be calculated accurately. The proposed method is compared with the existing method in terms of the accuracy of the detected corner points. The proposed method accurately detects corner points even when the existing method fails. For high-resolution frames of 3.5mega-pixels, the proposed method is performed in 89.01ms.

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Adaptively Weighted Histogram based Local Contrast Enhancement (적응적으로 가중된 히스토그램 기반 지역적 대조비 향상 기법)

  • Lim, Seokjae;Kim, Wonjun
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2019.06a
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    • pp.92-94
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    • 2019
  • 본 논문에서는 서브 블록별 상대적 거리에 따라 적응적으로 가중된 히스토그램 기반 지역적 대조비 향상 기법을 제안한다. 기존 지역적 대조비 향상 기법은 제한적인 공간의 정보만을 이용하기 때문에 과잉 대조비 향상, 결과 영상의 부자연스러움을 초래하는 반면, 제안하는 방법은 서브 블록별 상대적 거리에 반비례하는 가중치를 통해 더 넓은 공간의 정보를 적응적으로 이용하여 과잉 대조비 향상, 결과 영상의 부자연스러움을 효과적으로 방지한다. 실험 결과를 통해 제안하는 방법은 지역적 특성을 강화해주는 동시에 전역적인 자연스러움을 보존하는 것을 확인할 수 있다.

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