• 제목/요약/키워드: Relative Histogram

검색결과 77건 처리시간 0.025초

Local-Based Iterative Histogram Matching for Relative Radiometric Normalization

  • Seo, Dae Kyo;Eo, Yang Dam
    • 한국측량학회지
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    • 제37권5호
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    • pp.323-330
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    • 2019
  • Radiometric normalization with multi-temporal satellite images is essential for time series analysis and change detection. Generally, relative radiometric normalization, which is an image-based method, is performed, and histogram matching is a representative method for normalizing the non-linear properties. However, since it utilizes global statistical information only, local information is not considered at all. Thus, this paper proposes a histogram matching method considering local information. The proposed method divides histograms based on density, mean, and standard deviation of image intensities, and performs histogram matching locally on the sub-histogram. The matched histogram is then further partitioned and this process is performed again, iteratively, controlled with the wasserstein distance. Finally, the proposed method is compared to global histogram matching. The experimental results show that the proposed method is visually and quantitatively superior to the conventional method, which indicates the applicability of the proposed method to the radiometric normalization of multi-temporal images with non-linear properties.

Rotation Invariant Histogram of Oriented Gradients

  • Cheon, Min-Kyu;Lee, Won-Ju;Hyun, Chang-Ho;Park, Mignon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제11권4호
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    • pp.293-298
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    • 2011
  • In this paper, we propose a new image descriptor, that is, a rotation invariant histogram of oriented gradients (RIHOG). RIHOG overcomes a disadvantage of the histogram of oriented gradients (HOG), which is very sensitive to image rotation. The HOG only uses magnitude values of a pixel without considering neighboring pixels. The RIHOG uses the accumulated relative magnitude values of corresponding relative orientation calculated with neighboring pixels, which has an effect on reducing the sensitivity to image rotation. The performance of RIHOG is verified via the index of classification and classification of Brodatz texture data.

히스토그램에 의한 마멸분의 형태분포에 관한 연구 (Study on Shape Distribution of Wear Particles with Histogram)

  • 조연상;문성동;박흥식
    • 대한기계학회논문집A
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    • 제32권11호
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    • pp.963-969
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    • 2008
  • The wear particles are relative to the failure and the life of machine elements directly. But it is not laid down to calculate shape parameters of wear particle. To analyze a variation of distributed characteristics of wear particles on moving conditions, its shape parameters such as diameter and roundness were calculated the quantitative values by digital image processing, and had to be defined the effective method of using those data. Up to the present, the shape parameters have been used simply into the average values. But these values are not effective to analyze a variation of distributed characteristics of occurred wear particles on moving conditions. In this study, the relative histograms of shape parameters of wear particles were used for the purpose of analyzing the distribution of wear particles in various conditions. The results showed that the relative histogram of shape parameters can be effectively represented to study a wear mechanism.

히스토그램과 퍼지 기법을 이용한 레이저 용접 결함 인식에 관한 연구 (A Study on Defect Recognition of Laser Welding using Histogram and Fuzzy Techniques)

  • 장영건
    • 전기전자학회논문지
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    • 제5권2호
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    • pp.190-200
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    • 2001
  • 본 논문은 용접이상을 검출하기 위한 특징벡터의 선택과 퍼지 기술을 사용한 용접이상 분류기의 설계 및 구현에 관한 것이다. 용접이상 특징 벡터로써 시간 영역에서 절대적분치, 영교차수를, 주파수 영역에서 파워 스펙트럼 계수를, 두 영역 모두를 고려하여 히스토그램을 비교하였다. 그래프 분석에 의하여 특징벡터로서 히스토그램을 선택하였고, 상대 히스토그램의 최대 빈도수와 대응 구간 값이 정상 용접과 용입불량을 구분하는 데 가장 유효하다는 것을 발견하였다. 이 특징 벡터를 사용하여 퍼지 용접이상 분류기를 구현하였고, 695개의 용접 데이터 프레임에 대하여 시험하여 정분류율이 92.96%을 보여, 그 유효성을 입증하였다. 실험실에서의 결과로써 실제적인 산업용 레이저 용접 검사기로써 상대적 히스토그램을 이용한 퍼지 용접이상 분류기가 효과적임을 알 수 있다.

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프레임간의 상대적인 차이를 이용한 비디오의 셔트 검출 기법 (Shot Boundary Detection Using Relative Difference between Two Frames)

  • 정인식;권오진
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2001년도 하계종합학술대회 논문집(4)
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    • pp.101-104
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    • 2001
  • This paper proposes a unique shot boundary detection algorithm for the video indexing and/or browsing. Conventional methods based on the frame differences and the histogram differences are improved. Instead of using absolute frame differences, block by block based relative frame differences are employed. Frame adaptive thresholding values are also employed for the better detection. for the cases that the frame differences are not enough to detect the shot boundary, histogram differences are selectively applied. Experimental results show that the proposed algorithm reduces both the “false positive” errors and the “false negative” errors especially for the videos of dynamic local and/or global motions

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Automatic Contrast Enhancement by Transfer Function Modification

  • Bae, Tae Wuk;Ahn, Sang Ho;Altunbasak, Yucel
    • ETRI Journal
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    • 제39권1호
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    • pp.76-86
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    • 2017
  • In this study, we propose an automatic contrast enhancement method based on transfer function modification (TFM) by histogram equalization. Previous histogram-based global contrast enhancement techniques employ histogram modification, whereas we propose a direct TFM technique that considers the mean brightness of an image during contrast enhancement. The mean point shifting method using a transfer function is proposed to preserve the mean brightness of an image. In addition, the linearization of transfer function technique, which has a histogram flattening effect, is designed to reduce visual artifacts. An attenuation factor is automatically determined using the maximum value of the probability density function in an image to control its rate of contrast. A new quantitative measurement method called sparsity of a histogram is proposed to obtain a better objective comparison relative to previous global contrast enhancement methods. According to our experimental results, we demonstrated the performance of our proposed method based on generalized measures and the newly proposed measurement.

화자 식별에서의 배경화자데이터를 이용한 히스토그램 등화 기법 (Histogram Equalization Using Background Speakers' Utterances for Speaker Identification)

  • 김명재;양일호;소병민;김민석;유하진
    • 말소리와 음성과학
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    • 제4권2호
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    • pp.79-86
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    • 2012
  • In this paper, we propose a novel approach to improve histogram equalization for speaker identification. Our method collects all speech features of UBM training data to make a reference distribution. The ranks of the feature vectors are calculated in the sorted list of the collection of the UBM training data and the test data. We use the ranks to perform order-based histogram equalization. The proposed method improves the accuracy of the speaker recognition system with short utterances. We use four kinds of speech databases to evaluate the proposed speaker recognition system and compare the system with cepstral mean normalization (CMN), mean and variance normalization (MVN), and histogram equalization (HEQ). Our system reduced the relative error rate by 33.3% from the baseline system.

Sea fog detection near Korea peninsula by using GMS-5 Satellite Data(A case study)

  • Chung, Hyo-Sang;Hwang, Byong-Jun;Kim, Young-Haw;Son, Eun-Ha
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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    • pp.214-218
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    • 1999
  • The aim of our study is to develop new algorism for sea fog detection by using Geostational Meteorological Satellite-5(GMS-5) and suggest the techniques of its continuous detection. So as to detect daytime sea fog/stratus(00UTC, May 10, 1999), visible accumulated histogram method and surface albedo method are used. The characteristic value during daytime showed A(min) > 20% and DA < 10% when visble accumulated histogram method was applied. And the sea fog region which detected is of similarity in composite image and surface albedo method. In case of nighttime sea fog(18UTC, May 10, 1999), infrared accumulated histogram method and maximum brightness temperature method are used, respectively. Maximum brightness temperature method(T_max method) detected sea fog better than IR accumulated histogram method. In case of T_max method, when infrared value is larger than T_max, fog is detected, where T_max is an unique value, maximum infrared value in each pixel during one month. Then T_max is beneath 700hpa temperature of GDAPS(Global Data Assimilation and Prediction System). Sea fog region which detected by T_max method was similar to the result of National Oceanic and Atmosheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) DCD(Dual Channel Difference). But inland visibility and relative humidity didn't always agreed well.

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Class-Based Histogram Equalization for Robust Speech Recognition

  • Suh, Young-Joo;Kim, Hoi-Rin
    • ETRI Journal
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    • 제28권4호
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    • pp.502-505
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    • 2006
  • A new class-based histogram equalization method is proposed for robust speech recognition. The proposed method aims at not only compensating the acoustic mismatch between training and test environments, but also at reducing the discrepancy between the phonetic distributions of training and test speech data. The algorithm utilizes multiple class-specific reference and test cumulative distribution functions, classifies the noisy test features into their corresponding classes, and equalizes the features by using their corresponding class-specific reference and test distributions. Experiments on the Aurora 2 database proved the effectiveness of the proposed method by reducing relative errors by 18.74%, 17.52%, and 23.45% over the conventional histogram equalization method and by 59.43%, 66.00%, and 50.50% over mel-cepstral-based features for test sets A, B, and C, respectively.

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공간 선택률 추정을 위한 압축 히스토그램 기법 (A Compressed Histogram Technique for Spatial Selectivity Estimation)

  • 정재두;지정희;류근호
    • 한국공간정보시스템학회:학술대회논문집
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    • 한국공간정보시스템학회 2004년도 국내 LBS 기술개발 및 표준화 동향세미나
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    • pp.69-74
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    • 2004
  • Selectivity estimation for spatial query is very important process in finding the most efficient execution plan. Many works have been performed to estimate accurately selectivity. Although they deal with some problems such as false-count, multi-count, they require a large amount of memory to retain accurate selectivity, so they can not get good results in little memory environments such as mobile-based small database. In order to solve this problem, we propose a new technique called MW histogram which is able to compress summary data and get reasonable results. It also has a flexible structure to react dynamic update. The experimental results showed that the MW histogram has lower relative error than MinSkew histogram and gets a good selectivity in little memory.

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