• 제목/요약/키워드: Local feature

검색결과 932건 처리시간 0.023초

국부 가중평균 질감단위를 이용한 새로운 질감인식 기법 (New Texture Recognition Method Using Local Weighting Averaged Texture Units)

  • 심재창;김기석;이준재;;하영호
    • 전자공학회논문지B
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    • 제31B권4호
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    • pp.129-137
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    • 1994
  • In this paper, a new texture feature extraction method for texture image classification is proposed. The proposed method is a modified texture spectrum method. It uses local weighting averaged texture unit, that is, the neighbor pixels are weithted and averaged in 4-direction and the calculated values are compared with center pixel to find texture units. The proposed method has only 81 texture units and these units are really good features for texture classification. The proposed method is applied to vegetable images and Blodatz album images and compared with several conventional methods for the feature extraction time and the recognition rate.

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Text Location and Extraction for Business Cards Using Stroke Width Estimation

  • Zhang, Cheng Dong;Lee, Guee-Sang
    • International Journal of Contents
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    • 제8권1호
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    • pp.30-38
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    • 2012
  • Text extraction and binarization are the important pre-processing steps for text recognition. The performance of text binarization strongly related to the accuracy of recognition stage. In our proposed method, the first stage based on line detection and shape feature analysis applied to locate the position of a business card and detect the shape from the complex environment. In the second stage, several local regions contained the possible text components are separated based on the projection histogram. In each local region, the pixels grouped into several connected components based on the connected component labeling and projection histogram. Then, classify each connect component into text region and reject the non-text region based on the feature information analysis such as size of connected component and stroke width estimation.

Enhanced Maximum Voiced Frequency Estimation Scheme for HTS Using Two-Band Excitation Model

  • Park, Jihoon;Hahn, Minsoo
    • ETRI Journal
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    • 제37권6호
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    • pp.1211-1219
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    • 2015
  • In a hidden Markov model-based speech synthesis system using a two-band excitation model, a maximum voiced frequency (MVF) is the most important feature as an excitation parameter because the synthetic speech quality depends on the MVF. This paper proposes an enhanced MVF estimation scheme based on a peak picking method. In the proposed scheme, both local peaks and peak lobes are picked from the spectrum of a linear predictive residual signal. The average of the normalized distances of local peaks and peak lobes is calculated and utilized as a feature to estimate an MVF. Experimental results of both objective and subjective tests show that the proposed scheme improves the synthetic speech quality compared with that of a conventional one in a mobile device as well as a PC environment.

변형된 지역 Gabor Feature를 이용한 VQ 기반의 영상 검색 (Image Retrieval using VQ based Local Modified Gabor Feature)

  • 신대규;김현술;박상희
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 하계학술대회 논문집 D
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    • pp.2634-2636
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    • 2001
  • This paper proposes a new method of retrieving images from large image databases. The method is based on VQ(Vector Quantization) of local texture information at interest points automatically detected in an image. The texture features are extracted by Gabor wavelet filter bank, and rearranged for rotation. These features are classified by VQ and then construct a pattern histogram. Retrievals are performed by just comparing pattern histograms between images. Experimental results have shown the robustness of the proposed method to image rotation, small scale change, noise addition and brightness change and also shown the possibility of the retrieval by a partial image.

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퍼지로직을 이용한 자율이동로봇의 최적경로계획 (Path Planning of Autonomous Mobile Robot Based on Fuzzy Logic Control)

  • 박종훈;이재광;허욱열
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 하계학술대회 논문집 D
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    • pp.2420-2422
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    • 2003
  • In this paper, two Fuzzy Logics for path planning of an autonomous mobile robot are proposed. If a target point is given, such problems regarding the velocity and object recognition are closely related with path to which the mobile robot navigates. Therefore, to ensure safety navigation of the mobile robot for two fuzzy logic parts, path planning considering the surrounding environment was performed in this paper. First, feature points for local and global path are determined by utilizing Cell Decomposition off-line computation. Second, the on-line robot using two Fuzzy Logics navigates around path when it tracks the feature points. We demonstrated optimized path planning only for local path using object recognition fuzzy logic corresponds to domestic situation. Furthermore, when navigating, the robot uses fuzzy logic for velocity and target angle. The proposed algorithms for path planning has been implemented and tested with pioneer-dxe mobile robot.

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Viewpoint Unconstrained Face Recognition Based on Affine Local Descriptors and Probabilistic Similarity

  • Gao, Yongbin;Lee, Hyo Jong
    • Journal of Information Processing Systems
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    • 제11권4호
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    • pp.643-654
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    • 2015
  • Face recognition under controlled settings, such as limited viewpoint and illumination change, can achieve good performance nowadays. However, real world application for face recognition is still challenging. In this paper, we propose using the combination of Affine Scale Invariant Feature Transform (SIFT) and Probabilistic Similarity for face recognition under a large viewpoint change. Affine SIFT is an extension of SIFT algorithm to detect affine invariant local descriptors. Affine SIFT generates a series of different viewpoints using affine transformation. In this way, it allows for a viewpoint difference between the gallery face and probe face. However, the human face is not planar as it contains significant 3D depth. Affine SIFT does not work well for significant change in pose. To complement this, we combined it with probabilistic similarity, which gets the log likelihood between the probe and gallery face based on sum of squared difference (SSD) distribution in an offline learning process. Our experiment results show that our framework achieves impressive better recognition accuracy than other algorithms compared on the FERET database.

지역 에너지 시스템의 계통 연계 및 독립 운전 특성에 관한 연구 (The Operating characteristics of Community Energy System(CES) with Grid connection and isolation)

  • 박용업;김광호;장성일
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 추계학술대회 논문집 전력기술부문
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    • pp.258-260
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    • 2004
  • This paper analyse a operating characteristics when the Community Energy System (CES) is operated islanding mode. In the near future, CES might be one of major energy supply structures. The basic concept of CES is that it supplies electrical and thermal energy to the local customer loads through the islanded power network separated from the grid. The CES must be supplying local load with stable energy on the islanding mode, analysing necessary to thoroughly the operation feature. In order to show them, in this paper, we model the CES with 2.34 MVA DG and simulate the operating feature on the islanding mode of CES. The simulation results show that, in order to stability operate, the CES need the efficient load management and generation control schemes during the transition periods.

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인터랙티브 TV 컨트롤 시스템을 위한 근적외선 영상의 얼굴 인식 (Face recognition of Intra-red Images for Interactive TV Control System)

  • 원철호;이상헌;이태균
    • 한국산업정보학회논문지
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    • 제15권5호
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    • pp.11-17
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    • 2010
  • 본 논문에서는 인터랙티브 TV 컨트롤 시스템(ITCS)에 적용될 수 있는 근적외선 얼굴 영상에 대한 얼굴인식 방법을 제안하였다. 근적외선 얼굴 영상에서 ULBP(uniform local binary pattern) 히스토그램 피쳐를 추출하고 SVM 판별기를 이용하여 좌우 눈좌표 및 얼굴 영역을 검출하였다. 또한, 가버 변환과 ULBP 히스토그램 피쳐를 이용한 얼굴인식 시스템을 구현하여 이를 인터랙티브 TV 컨트롤 시스템 개인 인증 과정에 사용하였다.

이미지 특징 추출연산자 DBAH/DBAG 와 하드웨어 실현 (Image Feature Extracting Operators Using DBAH/DBAG and its Implementation)

  • Cho, Sung-Mok
    • 한국컴퓨터정보학회논문지
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    • 제6권1호
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    • pp.31-37
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    • 2001
  • 인간의 시각현상은 밝은 영역보다 어두운 영역의 특징점 추출에 더 민감하다. 그러므로 특징점 추출 연산자는 인간의 시각체계와 유사하게 물체를 인식하기 위해 국부적인 밝기를 고려해야 한다. 일반적으로 지금까지의 특징점 추출 연산자는 계산량이 많거나 다변수를 이용해야 하는 문제점을 가지고 있다. 본 논문에서는 이러한 단점을 극복하는 새로운연산자가 제안된다. 이 연산자는 실현이 매우 간단할 뿐만 아니라 합성영상과 실영상에 적용한 결과 우수한 성능을 나타내었다.

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객체 추적을 위한 보틀넥 기반 Siam-CNN 알고리즘 (Bottleneck-based Siam-CNN Algorithm for Object Tracking)

  • 임수창;김종찬
    • 한국멀티미디어학회논문지
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    • 제25권1호
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    • pp.72-81
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    • 2022
  • Visual Object Tracking is known as the most fundamental problem in the field of computer vision. Object tracking localize the region of target object with bounding box in the video. In this paper, a custom CNN is created to extract object feature that has strong and various information. This network was constructed as a Siamese network for use as a feature extractor. The input images are passed convolution block composed of a bottleneck layers, and features are emphasized. The feature map of the target object and the search area, extracted from the Siamese network, was input as a local proposal network. Estimate the object area using the feature map. The performance of the tracking algorithm was evaluated using the OTB2013 dataset. Success Plot and Precision Plot were used as evaluation matrix. As a result of the experiment, 0.611 in Success Plot and 0.831 in Precision Plot were achieved.