• Title, Summary, Keyword: Image based

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Segmentation of Millimeter-wave Radiometer Image via Classuncertainty and Region-homogeneity

  • Singh, Manoj Kumar;Tiwary, U.S.;Kim, Yong-Hoon
    • Proceedings of the KSRS Conference
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    • pp.862-864
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    • 2003
  • Thresholding is a popular image segmentation method that converts a gray-level image into a binary image. The selection of optimum threshold has remained a challenge over decades. Many image segmentation techniques are developed using information about image in other space rather than the image space itself. Most of the technique based on histogram analysis information-theoretic approaches. In this paper, the criterion function for finding optimal threshold is developed using an intensity-based classuncertainty (a histogram-based property of an image) and region-homogeneity (an image morphology-based property). The theory of the optimum thresholding method is based on postulates that objects manifest themselves with fuzzy boundaries in any digital image acquired by an imaging device. The performance of the proposed method is illustrated on experimental data obtained by W-band millimeter-wave radiometer image under different noise level.

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Content-Based Image Retrieval System using Feature Extraction of Image Objects (영상 객체의 특징 추출을 이용한 내용 기반 영상 검색 시스템)

  • Jung Seh-Hwan;Seo Kwang-Kyu
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.27 no.3
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    • pp.59-65
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    • 2004
  • This paper explores an image segmentation and representation method using Vector Quantization(VQ) on color and texture for content-based image retrieval system. The basic idea is a transformation from the raw pixel data to a small set of image regions which are coherent in color and texture space. These schemes are used for object-based image retrieval. Features for image retrieval are three color features from HSV color model and five texture features from Gray-level co-occurrence matrices. Once the feature extraction scheme is performed in the image, 8-dimensional feature vectors represent each pixel in the image. VQ algorithm is used to cluster each pixel data into groups. A representative feature table based on the dominant groups is obtained and used to retrieve similar images according to object within the image. The proposed method can retrieve similar images even in the case that the objects are translated, scaled, and rotated.

GeoNet : Web-based Remotely Sensed Image Processing System

  • Yang, Jong-Yoon;Ahn, Chung-Hyun;Kim, Kyoung-Ok
    • Proceedings of the KSRS Conference
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    • pp.165-170
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    • 1999
  • Previous technology of remote sensing was focused on analyzing raster image and gaining information through image processing. But now it has extended to diverse fields like automatic map generation, material exploitation or monitoring environmental changes with effort to utilizing practical usage. And with rapid expansion of information exchange on Internet and high-speed network, the demand of public which want to utilize remotely sensed image has been increased. This makes growth of service on acquisition and processing remotely sensed image. GeoNet is a Java-based remotely sensed image processing system. It is based on Java object-oriented paradigm and features cross-platform, web-based execution and extensibility to client/server remotely sensed image processing model. Remotely sensed image processing software made by Java programming language can suggest alternatives to meet readily demand on remotely sensed image processing in proportion to increase of remotely sensed data. In this paper, we introduce GeoNet and explain its architecture.

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Automatic Registration between EO and IR Images of KOMPSAT-3A Using Block-based Image Matching

  • Kang, Hyungseok
    • Korean Journal of Remote Sensing
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    • v.36 no.4
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    • pp.545-555
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    • 2020
  • This paper focuses on automatic image registration between EO (Electro-Optical) and IR (InfraRed) satellite images with different spectral properties using block-based approach and simple preprocessing technique to enhance the performance of feature matching. If unpreprocessed EO and IR images from Kompsat-3A satellite were applied to local feature matching algorithms(Scale Invariant Feature Transform, Speed-Up Robust Feature, etc.), image registration algorithm generally failed because of few detected feature points or mismatched pairs despite of many detected feature points. In this paper, we proposed a new image registration method which improved the performance of feature matching with block-based registration process on 9-divided image and pre-processing technique based on adaptive histogram equalization. The proposed method showed better performance than without our proposed technique on visual inspection and I-RMSE. This study can be used for automatic image registration between various images acquired from different sensors.

Image-based Visual Servoing for Automatic Recharging of Mobile Robot (이동로봇의 자동충전을 위한 영상기반 비쥬얼 서보잉 방법)

  • Song, Ho-Bum;Cho, Jae-Seung
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.7
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    • pp.664-670
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    • 2007
  • This study deals with image-based visual servoing for automatic recharging of mobile robot. Because mobile robot must be recharged periodically, it is necessary to detect and move to docking station. Generally, laser scanner is used for detect of position of docking station. CCD Camera is also used for this purpose. In case of using cameras, the position-based visual servoing method is widely used. But position-based visual servoing method requires the accurate calibration and it is hard and complex work. Another method using cameras is image-based visual servoing. Recently, image based visual servoing is widely used for robotic application. But it has a problem that cannot have linear trajectory in the 3-dimensional space. Because of this weak point, image-based visual servoing has a limit for real application. In case of 2-dimensional movement on the plane, it has also similar problem. In order to solve this problem, we point out the main reason of the problem of the resolved rate control method that has been generally used in the image-based visual servoing and we propose an image-based visual servoing method that can reduce the curved trajectory of mobile robot in the cartesian space.

An Improved Histogram-Based Image Hash (Histogram에 기반한 Image Hash 개선)

  • Kim, So-Young;Kim, Hyoung-Joong
    • 한국정보통신설비학회:학술대회논문집
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    • pp.531-534
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    • 2008
  • Image Hash specifies as a descriptor that can be used to measure similarity in images. Among all image Hash methods, histogram based image Hash has robustness to common noise-like operation and various geometric except histogram _equalization. In this_paper an improved histogram based Image Hash that is using "Imadjust" filter I together is proposed. This paper has achieved a satisfactory performance level on histogram equalization as well as geometric deformation.

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Framework for Content-Based Image Identification with Standardized Multiview Features

  • Das, Rik;Thepade, Sudeep;Ghosh, Saurav
    • ETRI Journal
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    • v.38 no.1
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    • pp.174-184
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    • 2016
  • Information identification with image data by means of low-level visual features has evolved as a challenging research domain. Conventional text-based mapping of image data has been gradually replaced by content-based techniques of image identification. Feature extraction from image content plays a crucial role in facilitating content-based detection processes. In this paper, the authors have proposed four different techniques for multiview feature extraction from images. The efficiency of extracted feature vectors for content-based image classification and retrieval is evaluated by means of fusion-based and data standardization-based techniques. It is observed that the latter surpasses the former. The proposed methods outclass state-of-the-art techniques for content-based image identification and show an average increase in precision of 17.71% and 22.78% for classification and retrieval, respectively. Three public datasets - Wang; Oliva and Torralba (OT-Scene); and Corel - are used for verification purposes. The research findings are statistically validated by conducting a paired t-test.

Content Based Image Retrieval Based on A Novel Image Block Technique Combining Color and Edge Features

  • Kwon, Goo-Rak;Haoming, Zou;Park, Sei-Seung
    • Journal of information and communication convergence engineering
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    • v.8 no.2
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    • pp.185-190
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    • 2010
  • In this paper we propose the CBIR algorithm which is based on a novel image block method that combined both color and edge feature. The main drawback of global histogram representation is dependent of the color without spatial or shape information, a new image block method that divided the image to 8 related blocks which contained more information of the image is utilized to extract image feature. Based on these 8 blocks, histogram equalization and edge detection techniques are also used for image retrieval. The experimental results show that the proposed image block method has better ability of characterizing the image contents than traditional block method and can perform the retrieval system efficiently.

Object-Based Image Search Using Color and Texture Homogeneous Regions (유사한 색상과 질감영역을 이용한 객체기반 영상검색)

  • 유헌우;장동식;서광규
    • Journal of Institute of Control, Robotics and Systems
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    • v.8 no.6
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    • pp.455-461
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    • 2002
  • Object-based image retrieval method is addressed. A new image segmentation algorithm and image comparing method between segmented objects are proposed. For image segmentation, color and texture features are extracted from each pixel in the image. These features we used as inputs into VQ (Vector Quantization) clustering method, which yields homogeneous objects in terns of color and texture. In this procedure, colors are quantized into a few dominant colors for simple representation and efficient retrieval. In retrieval case, two comparing schemes are proposed. Comparing between one query object and multi objects of a database image and comparing between multi query objects and multi objects of a database image are proposed. For fast retrieval, dominant object colors are key-indexed into database.

Image Adaptive LCD Backlight Boosting and Dimming For Perceptual Image Quality Enhancement (감성 화질 향상을 위한 이미지 적응형 LCD 백라이트 부스팅 및 디밍)

  • Lee, Chulhee;You, Jaehee
    • Journal of Korea Multimedia Society
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    • v.22 no.8
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    • pp.860-873
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    • 2019
  • LCD backlight boosting and the integration of boosting and dimming are proposed based on image analysis to maximize perceptual image qualities and to reduce display system power. Based on the histogram of the image data, methods for selecting an image suitable for boosting and for adjusting the optimum backlight brightness are proposed. A comprehensive combined optimization method of LCD backlight boosting, dimming and bypass based on image characteristics is also described. Perceptual image quality enhancement and power consumption are evaluated based on well known image databases. Average subjective image quality is improved by 24.8%, RMS contrast is improved more than 20%, and average power consumption is reduced by 15.94% compared to conventional uniform boosting.