• Title/Summary/Keyword: Hierarchical image tree model

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Weather Classification and Fog Detection using Hierarchical Image Tree Model and k-mean Segmentation in Single Outdoor Image (싱글 야외 영상에서 계층적 이미지 트리 모델과 k-평균 세분화를 이용한 날씨 분류와 안개 검출)

  • Park, Ki-Hong
    • Journal of Digital Contents Society
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    • v.18 no.8
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    • pp.1635-1640
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    • 2017
  • In this paper, a hierarchical image tree model for weather classification is defined in a single outdoor image, and a weather classification algorithm using image intensity and k-mean segmentation image is proposed. In the first level of the hierarchical image tree model, the indoor and outdoor images are distinguished. Whether the outdoor image is daytime, night, or sunrise/sunset image is judged using the intensity and the k-means segmentation image at the second level. In the last level, if it is classified as daytime image at the second level, it is finally estimated whether it is sunny or foggy image based on edge map and fog rate. Some experiments are conducted so as to verify the weather classification, and as a result, the proposed method shows that weather features are effectively detected in a given image.

Tree-Based Static/Dynamic Image Mosaicing (트리 기반 정적/동적 영상 모자이크)

  • Kang, Oh-hyung;Rhee, Yang-won
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.4
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    • pp.758-766
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    • 2003
  • This paper proposes a tree-based hierarchical image mosaicing system using camera and object parameters for efficient video database construction. Gray level histogram difference and average intensity difference are proposed for scene change detection of input video. Camera parameter measured by utilizing least sum of square difference and affine model, and difference image is used for similarity measure of two input images. Also, dynamic objects are searched by through macro block setting and extracted by using region splitting and 4-split detection methods. Dynamic trajectory evaluation function is used for expression of dynamic objects, and blurring is performed for construction of soft and slow mosaic image.

Motivation-based Hierarchical Behavior Planning

  • Song, Wei;Cho, Kyung-Eun;Um, Ky-Hyun
    • Journal of Korea Game Society
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    • v.8 no.1
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    • pp.79-90
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    • 2008
  • This paper describes a motivation-based hierarchical behavior planning framework to allow autonomous agents to select adaptive actions in simulation game environments. The combined behavior planning system is formed by four levels of specification, which are motivation extraction, goal list generation, action list determination and optimization. Our model increases the complexity of virtual human behavior planning by adding motivation with sudden and cumulative attributes. The motivation selection by probability distribution allows NPC to make multiple decisions in certain situations in order to embody realistic virtual humans. Hierarchical goal tree enhances the effective reactivity. Optimizing for potential actions provides NPC with safe and satisfying actions to adapt to the virtual environment. A restaurant simulation game was used to elucidate the mechanism of the framework.

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A Hierarchical Image Mosaicing using Camera and Object Parameters for Efficient Video Database Construction (효율적인 비디오 데이터베이스 구축을 위해 카메라와 객체 파라미터를 이용한 계층형 영상 모자이크)

  • 신성윤;이양원
    • Journal of Korea Multimedia Society
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    • v.5 no.2
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    • pp.167-175
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    • 2002
  • Image Mosaicing creates a new image by composing video frames or still images that are related, and performed by arrangement, composition and redundancy analysis of images. This paper proposes a hierarchical image mosaicing system using camera and object parameters far efficient video database construction. A tree-based image mosiacing has implemented for high-speed computation time and for construction of static and dynamic image mosaic. Camera parameters are measured by using least sum of squared difference and affine model. Dynamic object detection algorithm has proposed for extracting dynamic objects. For object extraction, difference image, macro block, region splitting and 4-split detection methods are proposed and used. Also, a dynamic positioning method is used for presenting dynamic objects and a blurring method is used for creating flexible mosaic image.

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Template Recovery of DWT-DFT Composite Watermarking Scheme Using Collinear Cross-Ratio

  • Sepsirisuk, Kasemsuk;Atsuta, Kiyoaki;Kondo, Shozo
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.225-228
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    • 2005
  • According to a popularization of the Internet and digital lifestyle, digital watermarks have been proposed for protection of copyrighted multimedia content. In blind watermark detection, which an original image is not provided, robustness against geometric distortion and compression remains challenging. In this paper, we propose a new perceptual blind discrete wavelet transform - discrete Fourier transform (DWT-DFT) composite watermarking scheme that is robust against both general linear transform and JPEG compression. This algorithm constructs an image-dependent watermark in the most significant DWT coefficients, which is determined by using a hierarchical tree structure. Strength of watermark is determined from a just-noticeable difference (JND) profile of a perceptual model. Furthermore, a desired template is inserted into DFT domain of the watermarked image. In new manner, a cross-ratio of four collinear points is used for detecting the template. Experimental results have showed that the proposed scheme is robust against general linear distortion, JPEG compression and various general kinds of attacks in the Stirmark 3.1 watermark evaluation tool.

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Applicability of Geo-spatial Processing Open Sources to Geographic Object-based Image Analysis (GEOBIA)

  • Lee, Ki-Won;Kang, Sang-Goo
    • Korean Journal of Remote Sensing
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    • v.27 no.3
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    • pp.379-388
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    • 2011
  • At present, GEOBIA (Geographic Object-based Image Analysis), heir of OBIA (Object-based Image Analysis), is regarded as an important methodology by object-oriented paradigm for remote sensing, dealing with geo-objects related to image segmentation and classification in the different view point of pixel-based processing. This also helps to directly link to GIS applications. Thus, GEOBIA software is on the booming. The main theme of this study is to look into the applicability of geo-spatial processing open source to GEOBIA. However, there is no few fully featured open source for GEOBIA which needs complicated schemes and algorithms, till It was carried out to implement a preliminary system for GEOBIA running an integrated and user-oriented environment. This work was performed by using various open sources such as OTB or PostgreSQL/PostGIS. Some points are different from the widely-used proprietary GEOBIA software. In this system, geo-objects are not file-based ones, but tightly linked with GIS layers in spatial database management system. The mean shift algorithm with parameters associated with spatial similarities or homogeneities is used for image segmentation. For classification process in this work, tree-based model of hierarchical network composing parent and child nodes is implemented by attribute join in the semi-automatic mode, unlike traditional image-based classification. Of course, this integrated GEOBIA system is on the progressing stage, and further works are necessary. It is expected that this approach helps to develop and to extend new applications such as urban mapping or change detection linked to GIS data sets using GEOBIA.