• Title/Summary/Keyword: histogram data

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A Study of the 3D-Reconstruction of indoor using Stereo Camera System (스테레오 카메라를 이용한 실내환경의 3차원 복원에 관한 연구)

  • Lee Dong-Hun;Um Dae-Youn;Kang Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.1
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    • pp.42-47
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    • 2005
  • In this papcr, we address the 3D reconstruction of the indoor circumstance using what the data is extracted by a pall of image from Stereo Camera. Generally sucaking, there arc three methods to extract 3-Dimensional data using IR sensor, Laser sensor and Stereo camera sensor. The best is stereo camera sensor which can show a high performance at a reasonable price. We used 'Window Correlation Matching Method' to extract 3-Dimensional data in stereo image. We proposed new Method to reduce error data, said 'Histogram Weighted Hough Transform'. Owing to this mettled, we reduced error data in each stereo image. So reconstruction is well done. 3-Dimensional Reconstruction is accomplished by using the DirectX that is well known as 3D-Game development tool. We show that the stereo camera can be not only used to extract 3-dimensional data but also applied to reconstruct the 3-Dimensional circumstance. And we try to reduce the error data using various method.

A Broken Image Screening Method based on Histogram Analysis to Improve GAN Algorithm (GAN 알고리즘 개선을 위한 히스토그램 분석 기반 파손 영상 선별 방법)

  • Cho, Jin-Hwan;Jang, Jongwook;Jang, Si-Woong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.4
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    • pp.591-597
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    • 2022
  • Recently, many studies have been done on the data augmentation technique as a way to efficiently build datasets. Among them, a representative data augmentation technique is a method of utilizing Generative Adversarial Network (GAN), which generates data similar to real data by competitively learning generators and discriminators. However, when learning GAN, there are cases where a broken pixel image occurs among similar data generated according to the environment and progress, which cannot be used as a dataset and causes an increase in learning time. In this paper, an algorithm was developed to select these damaged images by analyzing the histogram of image data generated during the GAN learning process, and as a result of comparing them with the images generated in the existing GAN, the ratio of the damaged images was reduced by 33.3 times(3,330%).

Adult Image Filtering using Support Vector Mchine (Support Vector Machine을 이용한 유해 이미지 분류)

  • Song, Chull-Hwan;Yoo, Seong-Joon
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.10c
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    • pp.218-221
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    • 2006
  • 본 논문은 인터넷의 대표적인 문제점중의 하나인 Adult Image 분류 연구에 대해 기술한다. 특히 우리는 이러한 Adult Image를 분류하기 위한 Data Set을 5가지 타입으로 구성한다. 이러한 각 Image에 대해 Color, Gradient, Edge Direction 특성의 Feature들을 추출하고 이를 Histogram으로 구성한다. 이렇게 구성된 Histogram을 Support Vector Machine에 적용하여 Adult Image를 분류한다. 그 결과, 우리는 8250개의 Test Set에 대하여 Recall(96.53%), Precision(97.33%), False Positive(2.96%), F-Measure(96.93%)의 성능 결과를 보여준다.

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Study on analysis of initial Data on 6 Sigma application in real fields (6 Sigma 현장적용 적용 시 초기 데이터 분석에 대한 고찰)

  • Lee, Sang-Bok;Choe, Eun-Hyang
    • Proceedings of the Korean Society for Quality Management Conference
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    • 2009.10a
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    • pp.33-39
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    • 2009
  • 본 연구에서는 현장에서 6 시그마를 활용 시 통계분석의 기초가 되는 초기 데이터 분석에 대한 고찰이다. 통계의 가장 기본이 되는 데이터가 잘못되었으면 나머지 모두 문제가 된다. 이에 데이터 초기에 발생할 수 있는 여러 오류의 가능성을 살펴보고 각각에 대해 해결책을 제시하였다. 여기서 활용하는 방법들은 계측기 선정, Gage R&R, Histogram, Box-plot, PDF, Box-Cox 변화 등이다.

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The Survey of Observer′s Preference Based on the Different Histogram algorithm Method (히스토그램변환 방법에 따른 관측자들의 선호도 조사)

  • 정재영;김대희;홍상기;조맹섭
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.271-274
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    • 2002
  • The YCbCr color is widely used for digital video. In this paper, six different histogram algorithms are defined; the corresponding test images are then produced; and these images are then evaluated by observers using psychophysical techniques such as pair comparison; and show observer's preference data based on the psychophysical experiment.

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Reversible DNA Watermarking Technique Using Histogram Shifting for Bio-Security (바이오 정보보호 위한 히스토그램 쉬프팅 기반 가역성 DNA 워터마킹 기법)

  • Lee, Suk-Hwan;Kwon, Seong-Geun;Lee, Eung-Joo;Kwon, Ki-Ryong
    • Journal of Korea Multimedia Society
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    • v.20 no.2
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    • pp.244-253
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    • 2017
  • Reversible DNA watermarking is capable of continuous DNA storage and forgery prevention, and has the advantage of being able to analyze biological mutation processes by external watermarking by iterative process of concealment and restoration. In this paper, we propose a reversible DNA watermarking method based on histogram multiple shifting of noncoding DNA sequence that can prevent false start codon, maintain original sequence length, maintain high watermark capacity without biologic mutation. The proposed method transforms the non-coding region DNA sequence to the n-th code coefficients and embeds the multiple bits of the n-th code coefficients by the non-recursive histogram multiple shifting method. The multi-bit embedding process prevents the false start codon generation through comparison search between adjacent concealed nucleotide sequences. From the experimental results, it was confirmed that the proposed method has higher watermark capacity of 0.004-0.382 bpn than the conventional method and has higher watermark capacity than the additional data. Also, it was confirmed that false start codon was not generated unlike the conventional method.

Video Abstracting Using Scene Change Detection and Shot Clustering for Construction of Efficient Video Database (대용량 비디오 데이터베이스 구축을 위하여 장면전환 검출과 샷 클러스터링을 이용한 비디오 개요 추출)

  • Shin Seong-Yoon;Pyo Seong-Bae
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.2 s.40
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    • pp.111-119
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    • 2006
  • Video viewers can not understand enough entire video contents because most video is long length data of large capacity. This paper propose efficient scene change detection and video abstracting using new shot clustering to solve this problem. Scene change detection is extracted by method that was merged color histogram with $\chi2$ histogram. Clustering is performed by similarity measure using difference of local histogram and new shot merge algorithm. Furthermore, experimental result is represented by using Real TV broadcast program.

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Video Abstracting Construction of Efficient Video Database (대용량 비디오 데이터베이스 구축을 위한 비디오 개요 추출)

  • Shin Seong-Yoon;Pyo Seong-Bae;Rhee Yang-Won
    • KSCI Review
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    • v.14 no.1
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    • pp.255-264
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    • 2006
  • Video viewers can not understand enough entire video contents because most video is long length data of large capacity. This paper propose efficient scene change detection and video abstracting using new shot clustering to solve this problem. Scene change detection is extracted by method that was merged color histogram with ${\chi}^2$ histogram. Clustering is performed by similarity measure using difference of local histogram and new shot merge algorithm. Furthermore, experimental result is represented by using Real TV broadcast program.

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Noise Robust Automatic Speech Recognition Scheme with Histogram of Oriented Gradient Features

  • Park, Taejin;Beack, SeungKwan;Lee, Taejin
    • IEIE Transactions on Smart Processing and Computing
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    • v.3 no.5
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    • pp.259-266
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    • 2014
  • In this paper, we propose a novel technique for noise robust automatic speech recognition (ASR). The development of ASR techniques has made it possible to recognize isolated words with a near perfect word recognition rate. However, in a highly noisy environment, a distinct mismatch between the trained speech and the test data results in a significantly degraded word recognition rate (WRA). Unlike conventional ASR systems employing Mel-frequency cepstral coefficients (MFCCs) and a hidden Markov model (HMM), this study employ histogram of oriented gradient (HOG) features and a Support Vector Machine (SVM) to ASR tasks to overcome this problem. Our proposed ASR system is less vulnerable to external interference noise, and achieves a higher WRA compared to a conventional ASR system equipped with MFCCs and an HMM. The performance of our proposed ASR system was evaluated using a phonetically balanced word (PBW) set mixed with artificially added noise.

The Implementing a Color, Edge, Optical Flow based on Mixed Algorithm for Shot Boundary Improvement (샷 경계검출 개선을 위한 칼라, 엣지, 옵티컬플로우 기반의 혼합형 알고리즘 구현)

  • Park, Seo Rin;Lim, Yang Mi
    • Journal of Korea Multimedia Society
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    • v.21 no.8
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    • pp.829-836
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    • 2018
  • This study attempts to detect a shot boundary in films(or dramas) based on the length of a sequence. As films or dramas use scene change effects a lot, the issues regarding the effects are more diverse than those used in surveillance cameras, sports videos, medical care and security. Visual techniques used in films are focused on the human sense of aesthetic therefore, it is difficult to solve the errors in shot boundary detection with the method employed in surveillance cameras. In order to define the errors arisen from the scene change effects between the images and resolve those issues, the mixed algorithm based upon color histogram, edge histogram, and optical flow was implemented. The shot boundary data from this study will be used when analysing the configuration of meaningful shots in sequences in the future.