• Title/Summary/Keyword: Patch image

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A Study on Design for Casual Look Applying Painting Images of Henri Matisse (앙리 마티스 회화 이미지를 응용한 캐쥬얼 룩 디자인 연구)

  • Sim, Mi-Jung;Yu, Kum-Wha
    • The Research Journal of the Costume Culture
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    • v.18 no.4
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    • pp.612-625
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    • 2010
  • People have more expectations for arts and design and accordingly, various artworks were combined with fashion to meet the consumer needs. As people live a decent life, the development of leisure activities and industry has a much effect on apparel. With this phenomenon, a free and active casual look is making progress centering around the practical apparel, pursuing diversified efficiency irrespective of a season and considering sensibility not formality. In this study, paintings of Henri Matisse were analyzed in every respect and were applied in apparel design with diverse color arrangement and a motif originating in the phenomenon of modern fashion design which leads to the integration of arts and design. Painting image and color of Henri Matisse were used. Sportive casual and cultural casual was used in design as well. Originality of its color in the paintings which were used an a motif is coming from Gauguin and Gogh. Henri had influenced to the next generation with pursuit of violent color. The following conclusions were drawn from this study. First, the color of Henri Matisse's paintings has a strong contrast effect. It combines notable violent color with a simple yet decorative motif. Therefore color from Matisse's paintings suit for apparel of marked individuality with its free color arrangement. Second, free and active image in Henri Matisse's paintings is easy to express efficiency and popularity. It accords with the feature of casual wear. Third, through adding a flowing curved line in Henri Matisse's paintings to materials and applying various colors putting into a curved line image to a rib section, a decorative effect which goes with the whole shape is obtained. This study presents possibility of emergence of unique design using free color arrangement and motif from the image of paintings and aims development of modern fashion design in accordance with modern fashion giving importance to the difference and sensibility by integration of modern garments and artworks.

Single Image Haze Removal Technique via Pixel-based Joint BDCP and Hierarchical Bilateral Filter (픽셀 기반 Joint BDCP와 계층적 양방향 필터를 적용한 단일 영상 기반 안개 제거 기법)

  • Oh, Won-Geun;Kim, Jong-Ho
    • The Journal of the Korea institute of electronic communication sciences
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    • v.14 no.1
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    • pp.257-264
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    • 2019
  • This paper presents a single image haze removal method via a pixel-based joint BDCP (bright and dark channel prior) and a hierarchical bilateral filter in order to reduce computational complexity and memory requirement while improving the dehazing performance. Pixel-based joint BDCP reduces the computational complexity compared to the patch-based DCP, while making it possible to estimate the atmospheric light in pixel unit and the transmission more accurately. Moreover the bilateral filter, which can smooth an image effectively while preserving edges, refines the transmission to reduce the halo effects, and its hierarchical structure applied to edges only prevents the increase of complexity from the iterative application. Experimental results on various hazy images show that the proposed method exhibits excellent haze removal performance with low computational complexity compared to the conventional methods, and thus it can be applied in various fields.

A Novel RGB Channel Assimilation for Hyperspectral Image Classification using 3D-Convolutional Neural Network with Bi-Long Short-Term Memory

  • M. Preethi;C. Velayutham;S. Arumugaperumal
    • International Journal of Computer Science & Network Security
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    • v.23 no.3
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    • pp.177-186
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    • 2023
  • Hyperspectral imaging technology is one of the most efficient and fast-growing technologies in recent years. Hyperspectral image (HSI) comprises contiguous spectral bands for every pixel that is used to detect the object with significant accuracy and details. HSI contains high dimensionality of spectral information which is not easy to classify every pixel. To confront the problem, we propose a novel RGB channel Assimilation for classification methods. The color features are extracted by using chromaticity computation. Additionally, this work discusses the classification of hyperspectral image based on Domain Transform Interpolated Convolution Filter (DTICF) and 3D-CNN with Bi-directional-Long Short Term Memory (Bi-LSTM). There are three steps for the proposed techniques: First, HSI data is converted to RGB images with spatial features. Before using the DTICF, the RGB images of HSI and patch of the input image from raw HSI are integrated. Afterward, the pair features of spectral and spatial are excerpted using DTICF from integrated HSI. Those obtained spatial and spectral features are finally given into the designed 3D-CNN with Bi-LSTM framework. In the second step, the excerpted color features are classified by 2D-CNN. The probabilistic classification map of 3D-CNN-Bi-LSTM, and 2D-CNN are fused. In the last step, additionally, Markov Random Field (MRF) is utilized for improving the fused probabilistic classification map efficiently. Based on the experimental results, two different hyperspectral images prove that novel RGB channel assimilation of DTICF-3D-CNN-Bi-LSTM approach is more important and provides good classification results compared to other classification approaches.

Patch based Multi-Exposure Image Fusion using Gamma Transformation (감마 변환을 이용한 패치 기반의 다중 노출 영상 융합)

  • Kim, Jihwan;Choi, Hyunho;Jeong, Jechang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2017.06a
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    • pp.59-62
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    • 2017
  • 본 논문에서는 평균 밝기 부분에 가중치 맵으로써 감마 변환에 기반한 선형 결합을 제안하고자 한다. 기존의 패치를 기반으로 한 가중치 맵은 평균 밝기 부분에서 영상 내 밝기 값이 한쪽으로 치우쳐 영상의 밝은 부분이 과포화 상태가 되어 세부 정보가 손실되는 단점이 있다. 이에 본 논문에서는 전역적 및 지역적 영상의 평균 밝기 값을 이용하여 감마 변환된 값을 선형 결합 시켜줌으로써 영역 내 세부 정보를 보존시키고 주관적 화질을 향상시켰다. 실험을 통해 결과를 분석하고 성능을 비교하여 기존 알고리듬에 비해 제안한 알고리듬이 우수함을 증명하였다.

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Extraction of Geometric Components of Buildings with Gradients-driven Properties

  • Seo, Su-Young;Kim, Byung-Guk
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.27 no.1
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    • pp.723-733
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    • 2009
  • This study proposes a sequence of procedures to extract building boundaries and planar patches through segmentation of rasterized lidar data. Although previous approaches to building extraction have been shown satisfactory, there still exist needs to increase the degree of automation. The methodologies proposed in this study are as follows: Firstly, lidar data are rasterized into grid form in order to exploit its rapid access to neighboring elevations and image operations. Secondly, propagation of errors in raw data is taken into account for in assessing the quality of gradients-driven properties and further in choosing suitable parameters. Thirdly, extraction of planar patches is conducted through a sequence of processes: histogram analysis, least squares fitting, and region merging. Experimental results show that the geometric components of building models could be extracted by the proposed approach in a streamlined way.

A Study on Application of UCR, GCR in Printing (인쇄물의 UCR, GCR 적용에 관한 연구)

  • Lee, Cheul-Soung;Koo, Chul-Whoi
    • Journal of the Korean Graphic Arts Communication Society
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    • v.22 no.2
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    • pp.83-100
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    • 2004
  • In this paper, the quantity of dot gain in off-set printing is estimated by using the method of UCR(under color removal) and GCR(gray component replacement) and the degree of dot gain is researched through measurement of dot coverage of each color patch at the output film that is variously applied to discretionary quantity of dot gain each line in screen in the printing for the process of color separation and at the offset printing. Also, the best appropriate quantity of dot gain treatment is examined by printing each line in screen for reproduction of colors.

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Segmentation and Classification of Range Data Using Phase Information of Gabor Fiter (Gabor 필터의 위상 정보를 이용한 거리 영상의 분할 및 분류)

  • 현기호;이광호;황병곤;조석제;하영호
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.27 no.8
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    • pp.1275-1283
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    • 1990
  • Perception of surfaces from range images plays a key role in 3-D object recognition. Recognition of 3-D objects from range images is performed by matching the perceived surface descriptions with stored object models. The first step of the 3-d object recognition from range images is image segmentation. In this paper, an approach for segmenting 3-D range images into symbolic surface descriptions using spatial Gabor filter is proposed. Since the phase of data has a lot of important information, the phase information with magnitude information can effectively segment the range imagery into regions satisfying a common homogeneity criterion. The phase and magnitude of Gabor filter can represent a unique featur vector at a point of range data. As a result, range images are trnasformed into feature vectors in 3-parameter representation. The methods not only to extract meaningful features but also to classify a patch information from range images is presented.

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Robust Visual Tracking using Search Area Estimation and Multi-channel Local Edge Pattern

  • Kim, Eun-Joon
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.7
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    • pp.47-54
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    • 2017
  • Recently, correlation filter based trackers have shown excellent tracking performance and computational efficiency. In order to enhance tracking performance in the correlation filter based tracker, search area which is image patch for finding target must include target. In this paper, two methods to discriminatively represent target in the search area are proposed. Firstly, search area location is estimated using pyramidal Lucas-Kanade algorithm. By estimating search area location before filtering, fast motion target can be included in the search area. Secondly, we investigate multi-channel Local Edge Pattern(LEP) which is insensitive to illumination and noise variation. Qualitative and quantitative experiments are performed with eight dataset, which includes ground truth. In comparison with method without search area estimation, our approach retain tracking for the fast motion target. Additionally, the proposed multi-channel LEP improves discriminative performance compare to existing features.

Thorax masculinization in a transsexual patient: Inferior pedicle mastectomy without an inverted T scar

  • Cely, Adriana Marcela Gonzalez;Triana, Carlos Enrique;Triana, Lina Maria
    • Archives of Plastic Surgery
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    • v.46 no.3
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    • pp.262-266
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    • 2019
  • Transsexual individuals with gender dysphoria or gender identity disorder are rare, with a prevalence reported to range from 0.002% to 0.014%. Studies have shown that mastectomy yields significant improvements in body image and self-esteem in female-to-male transsexual patients. In patients with grade III breast ptosis, mastectomy with a nipple-areolar complex (NAC) graft is the most commonly used technique, although it has several disadvantages. In the case described herein, a bilateral mastectomy preserving the NAC in an inferior pedicle was performed. Additionally, a thin superior thoracic dermal-fat flap was preserved and eventually sutured at the previous inframammary fold, preventing an inverted T scar. This case shows the advantage of this technique for preserving the blood supply and innervation of the NAC, with a low hypopigmentation risk. Furthermore, in this technique, the patch effect does not impair the results of the NAC graft, and there is no need to use an inverted T scar that may result in thoracic feminization.

Analog Gauge Reading with Image Patch-based Convolutional Neural Network (이미지 패치 기반 합성곱 신경망을 통한 아날로그 게이지 인식)

  • Minsu Kyeon;Seunghan Paek;Jong-II Park
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2022.11a
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    • pp.95-98
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    • 2022
  • 아날로그 게이지는 여전히 많은 산업 시설에서 사용되고 있지만, 게이지 값을 사람이 수동으로 읽기 때문에 정확히 측정하기 위해 많은 시간이 소모가 되는 문제점이 있다. 이러한 이유로 최근에는 합성곱 신경망을 사용하여 아날로그 게이지 값을 자동으로 인식하는 연구가 진행되고 있다. 그러나 대부분의 선행연구들은 게이지가 촬영된 영상을 그대로 입력으로 사용하고 있으며, 이러한 방법은 사람이 게이지를 읽는 과정을 고려하였을 때 불필요한 부분이 많다. 본 논문에서는 게이지 전체 이미지를 학습에 사용하지 않고, 게이지의 특정 이미지 패치 기반으로 아날로그 게이지 값을 인식하는 방법을 제안한다. 제안하는 방법은 게이지의 중심, 눈금의 최소, 최대, 지침의 좌표를 기반으로 이미지 패치를 생성하고 채널 축으로 병합하여 학습을 진행하였으며, 최종적으로게이지의 각도를 계산한다. 이는 게이지의 평균 각도 오차를 통해 제안한 방법이 게이지 값을 인식하는데 우수한 성능이 보였으며, 게이지 이미지에 장애물이 있는 경우에도 게이지 값을 인식할 수 있음을 확인하였다.

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