• 제목/요약/키워드: Image size

Search Result 3,687, Processing Time 0.032 seconds

The Visual Image Evaluation for the Dot Pattern Size and the Variation of Coloration in the Achromatic Color (무채색 물방울무늬의 크기와 배색변화에 따른 시각적 이미지 평가)

  • Kim, Sun-Mi;Jeong, Su-Jin
    • Journal of Fashion Business
    • /
    • v.12 no.4
    • /
    • pp.114-130
    • /
    • 2008
  • The purpose of this study is to investigate the effect of Dot Pattern Size(0.8, 1.8, 2.5, 5, 8), color combination(W/Bk, Bk/Gr, Gr/W), Area-Ratio(Background/Dot, Dot/Background) on wearing dot-printed dresses image. Sets of stimulus and response scales(7 point semantic) were used as experimental materials. The stimuli were 30 color pictures manipulated with the combination of Dot Pattern Size, color combination, and Area-Ratio using computer simulation. The subjects were 180 female undergraduates living in Gyeongnam-do. The data was analyzed by using SPSS program. Analyzing methods were ANOVA and LSD test. Image factor of the stimulus was composed of 5 different components, visibility, chastity, attractiveness, cuteness and feminity. Among them, the visibility and chastity were important. Each dimensional image was affected by dot pattern size, color combination and Area-Ratio. In the visibility image, color combination(W/Bk is the most effective) is more influential, the larger size is effective pattern. In the cuteness and feminity image, area ratio(low-brightness dot pattern is the more effective) is more effective than color combination or dot pattern size. Even the same dot pattern size and area was recognized as different image depending on the area ratio. According to the variation of dot pattern size, color combination and area-ratio, it was investigated that the images for a dress wearer were expressed diversely, were shown differently in image dimensions, and could be produced to different images.

Characteristic of size distribution of rock chip produced by rock cutting with a pick cutter

  • Jeong, Hoyoung;Jeon, Seokwon
    • Geomechanics and Engineering
    • /
    • v.15 no.3
    • /
    • pp.811-822
    • /
    • 2018
  • Chip size distribution can be used to evaluate the cutting efficiency and to characterize the cutting behavior of rock during cutting and fragmentation process. In this study, a series of linear cutting tests was performed to investigate the effect of cutting conditions (specifically cut spacing and penetration depth) on the production and size distribution of rock chips. Linyi sandstone from China was used in the linear cutting tests. After each run of linear cutting machine test, the rock chips were collected and their size distribution was analyzed using a sieving test and image processing. Image processing can rapidly and cost-effectively provide useful information of size distribution. Rosin-Rammer distribution pamameters, the coarseness index and the coefficients of uniformity and curvature were determined by image processing for different cutting conditions. The size of the rock chips was greatest at the optimum cut spacing, and the size distribution parameters were highly correlated with cutter forces and specific energy.

Analysis of Image Identifier Generation Methods for Various Size Patterns (크기 변화에 따른 정지영상 식별자 생성 분석)

  • Park, Je-Ho
    • Journal of the Semiconductor & Display Technology
    • /
    • v.9 no.4
    • /
    • pp.51-56
    • /
    • 2010
  • As the price of image acquisition component becomes low enough, the compact and easily accessible handheld devices are generally equipped with image acquisition functionality. This trend speeds up various applications in diverse areas such as image related services and software. Therefore users strongly need to identify their images effectively and efficiently so that the duplicated images are perceived as one physical entity. In order to handle this environment, we propose a number of methods that generate image identifiers utilizing fundamental image features. In this paper, we analyze the identifier generation methods in terms of various size patterns, especially for tiny size cases, since the small images does not contain abundant pixels for feature extraction. In this paper, experimental evaluation over identifier generation methods' behavior according to different sizes is demonstrated.

A Study on Binary Image Compression Using Morphological Skeleton (수리 형태학적 세선화를 이용한 이진 영상 압축)

  • 정기룡
    • Journal of the Korean Institute of Navigation
    • /
    • v.19 no.3
    • /
    • pp.21-28
    • /
    • 1995
  • Mathematical morphology skeleton image processing makes many partial skeleton image planes from an original binary image. And the original binary image can be reconstructed without any distortion by summing the first partial skeleton image plane and each dilated partial skeleton image planes using the same structuring element. Especially compression effects of Elias coding to the morphological globally minimal skeleton(GMS) image, is better than that of PCX and Huffman coding. And then this paper proposes mathematical morphological GMS image processing which can be applied to a binary image transmitting for facimile and big size(bigger than $64{\times}64$ size) bitmap fonts storing in a memory.

  • PDF

Droplet size measurement using image processing method (이미지프로세싱 기법을 이용한 액적크기 측정)

  • Lim Byoungjik;Jung Kihoon;Khil Taeock;Yoon Youngbin
    • Journal of the Korean Society of Visualization
    • /
    • v.2 no.1
    • /
    • pp.25-31
    • /
    • 2004
  • Droplet size is one of the most important parameter which controls the performance of the combustion system using liquid fuel or oxidizer. Droplet formation and its size are mainly affected by the injection velocity and ambient gas density. Recently, droplet size measurement was conducted by PDPA or Malvern particle analyzer using laser light. But at this paper image processing method was developed to measure droplet size. And its validation was investigated with reticle.

  • PDF

3-DIMENSIONAL TILING TECHNIQUE TO PROCESS HUGE SIZE HIGH RESOLUTION SATELLITE IMAGE SEAMLESSLY AND RAPIDLY

  • Jung, Chan-Gyu;Kim, Jun-Chul;Hwang, Hyun-Deok
    • Proceedings of the KSRS Conference
    • /
    • 2007.10a
    • /
    • pp.85-89
    • /
    • 2007
  • This paper presents the method to provide a fast service for user in image manipulation such as zooming and panning of huge size high resolution satellite image (e.g. Giga bytes per scene). The proposed technique is based on the hierarchical structure that has 3D-Tiling in horizontal and vertical direction to provide the image service more effectively than 2D-Tiling technique in the past does. The essence of the proposed technique is to create tiles that have optimum level of horizontal as well as vertical direction on the basis of current displaying area which changes as user manipulates huge image. So this technique provides seamless service, and will be very powerful and useful for manipulation of images of huge size without data conversion.

  • PDF

3-Dimensional Tiling Technique to Process Huge Size High Resolution Satellite Image Seamlessly and Rapidly

  • Kim, Jun-Chul;Jung, Chan-Gyu;Kim, Moon-Gyu
    • Korean Journal of Remote Sensing
    • /
    • v.23 no.5
    • /
    • pp.375-383
    • /
    • 2007
  • This paper presents the method to provide a fast service for user in image manipulation such as zooming and panning of huge size high resolution satellite image(e.g. Giga bytes per scene). The proposed technique is based on the hierarchical structure that has 3D-Tiling in horizontal and vertical direction to provide the image service more effectively than 2D-Tiling technique in the past does. The essence of the proposed technique is to create tiles of optimum level in real time on the basis of current displaying area, which change as user manipulates huge image. Consequently, this technique provides seamless service, and will be very powerful and useful for manipulation of images of huge size without data conversion.

A Study of Image Quality and Exposed Dose by Field Size Changing on CBCT (CBCT 촬영 시 조사야 조절에 따른 영상의 최적화 및 피폭선량에 관한 고찰)

  • Bang, Seung Jae;Kim, Young Yeon;Jeong, Il Seon;Kim, Jeong Soo;Kim, Young Gon
    • The Journal of Korean Society for Radiation Therapy
    • /
    • v.25 no.2
    • /
    • pp.175-180
    • /
    • 2013
  • Purpose: Modern radiation therapy technique such as IGRT has become a routine clinical practice on LINAC for decrease patient's set-up error. CBCT can be used to adjust patient set-up error and treat patient more accurately. The Purpose of this study is to evaluate field size of CBCT for improving Image quality and suggest reference date of CBCT field size. Materials and Methods: Image date were acquired using KV CBCT and Catphan phantom (Half fan and full fan mode were scanned from 2 ~16 cm, at intervals of 2 cm). Field size were categorized by Small field size (2 cm, 4 cm), Medium field size (8 cm, 10 cm), Large field size (more than 14 cm) and evaluate. To estimated the CTDi using CTDi phantom and Ion chamber. Results: CT number linearity of Small and Large field size are greater than Medium field size. Spatial resolution are not significantly different without Small field size. But half fan mode is more different than full fan mode. In full fan, except Medium field size, all field size exceed recommendation for HU uniformity. But half pan has stability for all field except Small field size. CTDi makes radical sign function graph in Medium field size. Conclusion: The worst result was given by Small field size for Image quality and practically. Medium field size can be useful to prevent patient from radiation exposure and give better Image quality. So this study recommends that Medium field size (8~10 cm) is more suitable for CBCT.

  • PDF

A Study of the Fractal Image Compression with a Quadtree Partioning Method and a HV Partitioning Method (Quadtree 분할방식과 HV 분할방식을 이용한 프랙탈 이미지 압축에 관한 연구)

  • Byun, Chae-Ung;Lee, Key-Seo;Chung, Chin-Hyun
    • Proceedings of the KIEE Conference
    • /
    • 1995.07b
    • /
    • pp.980-982
    • /
    • 1995
  • Image coding based on a fractal theory of iterated transformations presents highly compressed image. In this paper, we compress image using the partitioning method which devides image adaptively in horizon and vertical axis. This method can encode image more compactly than the quadtree partitioning method. The maximum range size can be selected as $32{\times}32$ blocks and the minimum size can be $4{\times}4$ blocks. And the domain size is twice as many as the range size.

  • PDF

Optimizing Image Size of Convolutional Neural Networks for Producing Remote Sensing-based Thematic Map

  • Jo, Hyun-Woo;Kim, Ji-Won;Lim, Chul-Hee;Song, Chol-Ho;Lee, Woo-Kyun
    • Korean Journal of Remote Sensing
    • /
    • v.34 no.4
    • /
    • pp.661-670
    • /
    • 2018
  • This study aims to develop a methodology of convolutional neural networks (CNNs) to produce thematic maps from remote sensing data. Optimizing the image size for CNNs was studied, since the size of the image affects to accuracy, working as hyper-parameter. The selected study area is Mt. Ung, located in Dangjin-si, Chungcheongnam-do, South Korea, consisting of both coniferous forest and deciduous forest. Spatial structure analysis and the classification of forest type using CNNs was carried in the study area at a diverse range of scales. As a result of the spatial structure analysis, it was found that the local variance (LV) was high, in the range of 7.65 m to 18.87 m, meaning that the size of objects in the image is likely to be with in this range. As a result of the classification, the image measuring 15.81 m, belonging to the range with highest LV values, had the highest classification accuracy of 85.09%. Also, there was a positive correlation between LV and the accuracy in the range under 15.81 m, which was judged to be the optimal image size. Therefore, the trial and error selection of the optimum image size could be minimized by choosing the result of the spatial structure analysis as the starting point. This study estimated the optimal image size for CNNs using spatial structure analysis and found that this can be used to promote the application of deep-learning in remote sensing.