• Title/Summary/Keyword: Man Image

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AN IMAGE SEGMENTATION LEVEL SET METHOD FOR BUILDING DETECTION

  • Konstantinos, Karantzalos;Demetre, Argialas
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.610-614
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    • 2006
  • In this paper the advanced method of geodesic active contours was developed for the task of building detection from aerial and satellite images. Automatic extraction of man-made structures including buildings, building blocks or roads from remote sensing data is useful for land use mapping, scene understanding, robotic navigation, image retrieval, surveillance, emergency management procedures, cadastral etc. A level set method based on a region-driven segmentation model was implemented with which building boundaries were detected, through this curve propagation technique. The essence of this approach is to optimize the position and the geometric form of the curve by measuring information along that curve, and within the regions that compose the image partition. To this end, one can consider uniform intensities inside objects and the background. Thus, given an initial position of the curve, one can determine global, region-driven functions and provide a statistical description of the inside and outside object area. The calculus of variations and a gradient descent method was used to optimize the variational functional by an iterative steady state process. Experimental results demonstrate the potential of the proposed processing scheme.

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An interactive image retrieval system: from symbolic to semantic

  • Lan Le Thi;Boucher Alain
    • Proceedings of the IEEK Conference
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    • summer
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    • pp.427-434
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    • 2004
  • In this paper, we present a overview of content-based image retrieval (CBIR) systems: its results and its problems. We propose our CBIR system currently based on color and texture. From the CBIR systems. we discuss the way to add semantic values in image retrieval systems. There are 3 ways for adding them: concept definition, machine learning and man-machine interaction. Along with this we introduce our preliminary results and discuss them in the goal of reaching semantic retrieval. Different result representation schemes are presented. At last, we present our work to build a complete annotated image database and our image annotaion program.

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Emotion Recognition by CCD Color Image

  • Joo, Young-Hoon;Lee, Sang-Yoon;Oh, Jae-Heung;Sim, Kwee-Bo
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.138.2-138
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    • 2001
  • This paper proposes the technique for recognizing the human´s emotion by using the CCD color image. To do this, we first acquire the color image from the CCD camera. And then propose the method for recognizing the expressing to be represented the structural correlation of man´s feature points(eyebrows, eye, nose, mouse), In the proposed method. Human´s emotion is divided into four emotion(surprise, anger, happiness, sadness). Finally, we have proven the effectiveness of the proposed method through the experimentation.

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A Study on Gender Images Expressed in Military Fashion - Basis on a Women's wear in the 1990's - (밀리터리 패션에 나타난 성적 이미지 연구 - 1990년대 여성복을 중심으로 -)

  • 채금석;이화정
    • Journal of the Korean Society of Costume
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    • v.52 no.1
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    • pp.103-115
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    • 2002
  • The purpose of this study is understanding modern woman's various aesthetic values and aesthetic sense through observing expression aspects of gender images in the 1990s military fashion and analyzing their aesthetic characteristics and formative factors. Gender images in military fashion have expressed the masculine image of authoritative image and offensive image and offensive image, and the feminine image of conservative image and ostentatious image, sensual image. The authoritative image showed authority and dignity of military uniform by using the classic military uniform's image. This spoke for desire of women to rise their position. Heroism and androcentrism affected as its formation factor. The offensive image destroyed original dignified image of military uniform by that resistance to authoritative image and existing gender identity appeared as way-out form and deconstructive expression. Anti-establishment spirit, resistance to gender identity, and deconstructionism affected as its formation factor. The conservative image expressed military fashion only with slim and soft silhouette, curved line, color, and simple details by magnifying feminity. Fallen man's authority affected as its formation factor. The ostentatious image expressed military fashion with magnifying accessories such as gold button and belt by women who wanted to display ostentatiously their social position and charm. The aspiration for class of elite affected as its formation factor. The sensual image intended to show erotic voluptuous beauty of woman's body by indirect and direct body exposure. Narcissism, desire to show, and sexual amusement affected as its formation factor.

Actual Images and Pursued Images and Purchase Behaviors for Clothing as Determined by Self-Image (자기 이미지에 따른 착용의복이미지, 추구의복이미지 및 의복구매행동)

  • 염인경;김미숙
    • The Research Journal of the Costume Culture
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    • v.12 no.1
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    • pp.90-103
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    • 2004
  • The purpose of the present study was to investigate images pursued and purchase behaviors for clothing as determined by self-image. Data were collected through a self-administered questionnaire survey from March 3 to March 11, 2003 from 600 female students attending universities in Seoul; 514 were used for the data analysis. Data were analyzed by chi-square analysis, t-test, ANOVA, correlation analysis, tics, cluster analysis and Duncan's multiple range test. Self image was defined six factors: social image, gay image, intellectual image, girlish image, iron nerves image, image like a man and was classified three group avail of six factor: commonness type, social brilliance type, immature boldness type. The results showed significant differences in images of actual clothing worn by self and in the clothing image pursued among the groups determined by the self image. Significant differences were also found in clothing purchase behaviors such as monthly clothing expenditure, shopping frequency, store types, and the clothing items often used for expressing self-image among the groups divided by self-image.

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Content-Based Image Retrieval using Color Feature of Region and Adaptive Color Histogram Bin Matching Method (영역의 컬러특징과 적응적 컬러 히스토그램 빈 매칭 방법을 이용한 내용기반 영상검색)

  • Park, Jung-Man;Yoo, Gi-Hyoung;Jang, Se-Young;Han, Deuk-Su;Kwak, Hoon-Sung
    • Proceedings of the KIEE Conference
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    • 2005.10b
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    • pp.364-366
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    • 2005
  • From the 90's, the image information retrieval methods have been on progress. As good examples of the methods, Conventional histogram method and merged-color histogram method were introduced. They could get good result in image retrieval. However, Conventional histogram method has disadvantages if the histogram is shifted as a result of intensity change. Merged-color histogram, also, causes more process so, it needs more time to retrieve images. In this paper, we propose an improved new method using Adaptive Color Histogram Bin Matching(AHB) in image retrieval. The proposed method has been tested and verified through a number of simulations using hundreds of images in a database. The simulation results have Quickly yielded the highly accurate candidate images in comparison to other retrieval methods. We show that AHB's can give superior results to color histograms for image retrieval.

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Classification of Fused SAR/EO Images Using Transformation of Fusion Classification Class Label

  • Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.28 no.6
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    • pp.671-682
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    • 2012
  • Strong backscattering features from high-resolution Synthetic Aperture Rader (SAR) image provide useful information to analyze earth surface characteristics such as man-made objects in urban areas. The SAR image has, however, some limitations on description of detail information in urban areas compared to optical images. In this paper, we propose a new classification method using a fused SAR and Electro-Optical (EO) image, which provides more informative classification result than that of a single-sensor SAR image classification. The experimental results showed that the proposed method achieved successful results in combination of the SAR image classification and EO image characteristics.

Improved image alignment algorithm based on projective invariant for aerial video stabilization

  • Yi, Meng;Guo, Bao-Long;Yan, Chun-Man
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.9
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    • pp.3177-3195
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    • 2014
  • In many moving object detection problems of an aerial video, accurate and robust stabilization is of critical importance. In this paper, a novel accurate image alignment algorithm for aerial electronic image stabilization (EIS) is described. The feature points are first selected using optimal derivative filters based Harris detector, which can improve differentiation accuracy and obtain the precise coordinates of feature points. Then we choose the Delaunay Triangulation edges to find the matching pairs between feature points in overlapping images. The most "useful" matching points that belong to the background are used to find the global transformation parameters using the projective invariant. Finally, intentional motion of the camera is accumulated for correction by Sage-Husa adaptive filtering. Experiment results illustrate that the proposed algorithm is applied to the aerial captured video sequences with various dynamic scenes for performance demonstrations.

Printmaking Style Effect using Image Processing Techniques (영상처리 기법을 이용한 판화 스타일 효과)

  • Kim, Seung-Wan;Gwun, Ou-Bong
    • The Journal of the Korea Contents Association
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    • v.10 no.4
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    • pp.76-83
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    • 2010
  • In this paper, we propose a method that converts a inputted real image to a image feeling like printmaking. That is, this method converts a inputted real image to man made rubber printmaking style image using image processing techniques such as spatial filters, image bit-block transfer, etc. The process is as follows. First, after detecting edges in source image, we get the first image by deleting noise lines and points, then by sharpening. Secondly, we get second image using the similar method to the first image. Finally, we blend the first and the second image by logical AND operation This processing enables us to represent rubber panel and knife effects. Also, the proposed method shows that double edge detecting is effective in enhancing line-width and removing the tiny lines.