• 제목/요약/키워드: gray scale image

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A Study on the Visual Images of Checked Pattern Shirts in Achromatic Color (무채색 체크무늬 셔츠의 시각적 이미지 연구)

  • Choi, Su-Koung
    • Korean Journal of Human Ecology
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    • v.19 no.2
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    • pp.399-407
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    • 2010
  • The purpose of this study was to investigate the visual images of shirts according to coloration and the interval of checked patterns. The experimental stimulus and questionnaires for scaling response were developed for this study. The stimuli were 12 color pictures, in which the gender, coloration(WG: white+gray, WK: white+black, GK: gray+black), and interval(0.5 cm, 1.5 cm, 3.5 cm, 5.5 cm) were manipulated. The 7-point rating scale was used for evaluation of the visual image. Data were obtained from 144 male college students and 144 female college students living in Gyeonggi, Gyeongnam, Seoul, Gwangju, Daegu, and Busan on December 2009. For data analysis, ANOVA and the Duncan-test were used by using the SPSS program. The results of this study were as follows; the visual images for shirts according to the coloration and interval of checked patterns consisted of four dimensions of attractiveness, appeal, youth, and modesty. Gender was the main factor when looking at attractiveness. Coloration had the main effect on appeal, youth, and modesty. Also, there was a significant interaction effect of gender and coloration on attractiveness, while there was a significant interaction effect of coloration and interval on modesty.

Heterogeneous Face Recognition Using Texture feature descriptors (텍스처 기술자들을 이용한 이질적 얼굴 인식 시스템)

  • Bae, Han Byeol;Lee, Sangyoun
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.14 no.3
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    • pp.208-214
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    • 2021
  • Recently, much of the intelligent security scenario and criminal investigation demands for matching photo and non-photo. Existing face recognition system can not sufficiently guarantee these needs. In this paper, we propose an algorithm to improve the performance of heterogeneous face recognition systems by reducing the different modality between sketches and photos of the same person. The proposed algorithm extracts each image's texture features through texture descriptors (gray level co-occurrence matrix, multiscale local binary pattern), and based on this, generates a transformation matrix through eigenfeature regularization and extraction techniques. The score value calculated between the vectors generated in this way finally recognizes the identity of the sketch image through the score normalization methods.

Detection of ridges and valleys using local min/max operations (Local min/max 연산을 이용한 ridge 및 valley의 검출)

  • 박중조;김경민;정순원;박귀태
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.5
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    • pp.118-126
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    • 1996
  • In object analysis by image processing, finding lines plays a universal role. And these lines can be easily found by detecting ridges and valleys in digital gray scale images. In this paper, a new method of detecting ridges and valleys by using local min/max operations was presented. This method detects ridges and valleys of desired width by using erosion and dilation properties of local min/max operations, and requires no information of ridge or valley direction. Therefore the method is efficient and computationally simple in comparision with the conventional analytical method.

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RGB Motion Segmentation using Background Subtraction based on AMF

  • Kim, Yoon-Ho
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.6 no.2
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    • pp.81-87
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    • 2013
  • Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter (AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

Rubbing Process Evaluation Method for The LCD Panel

  • Honoki, Hideyuki;Sakai, Kaoru;Kawabe, Shun'Ichi;Nakasu, Nobuaki
    • 한국정보디스플레이학회:학술대회논문집
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    • 2002.08a
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    • pp.115-117
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    • 2002
  • In order to realize a stable rubbing process for the liquid crystal panel, the authors investigated the quantitative evaluation method of rubbing process uniformity. The proposed method focuses on the relationship between the image quality of the LCD panel for gray scale images and the rubbing uniformity. The proposed method indicates rubbing uniformity using quantitative parameters of spots and hairlines on the LCD panel.

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A study on DTCNN hardware implementation for image processing (영상처리를 위한 DTCNN 하드웨어 구현에 관한 연구)

  • 문성용
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.4
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    • pp.96-104
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    • 1998
  • In this paper, the circuit of DTCNN designed using dilation and erosion operation, a basic operation of gray-scale morphology, also each cell designed PE in order to having extension using the local connectivity. In this PE design, connection of between cell and cell become simple. And it is realized to easily VLSI realization as well as to circuit to be parallel processing. As the resutls of simulations, the proposed method was verified to improved more operation speed than the sequential data processing, parallel processing DTCNN was implemented in a 0.8.mu.m CMOS technology using COMPASS Tool.

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RGB Motion Segmentation using Background Subtraction based on AMF

  • Kim, Yoon-Ho
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.7 no.1
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    • pp.61-67
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    • 2014
  • Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter(AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

The Study for Improvement of False Contour in the Plasma Display Panel (플라즈마 디스플레이 패널의 의사윤곽 개선에 관한 연구)

  • Shin, Jae-Hwa;Ha, Sung-Chul;Lee, Seok-Hyun
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.52 no.3
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    • pp.113-120
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    • 2003
  • Plasma display panels normally utilize the binary coded light emission scheme for gray scale expression. Subsequently, this expression method makes dynamic false contours. We propose the "E3DSM(enhanced 3-dimension scattering method)" that improved existing 3-d scattering method and the "HAM(histogram analysis method)" that is decided the driving schemes and subfield selections with histograms of images. Simulation results show the improving image quality.

Brain MR Multimodal Medical Image Registration Based on Image Segmentation and Symmetric Self-similarity

  • Yang, Zhenzhen;Kuang, Nan;Yang, Yongpeng;Kang, Bin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.3
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    • pp.1167-1187
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    • 2020
  • With the development of medical imaging technology, image registration has been widely used in the field of disease diagnosis. The registration between different modal images of brain magnetic resonance (MR) is particularly important for the diagnosis of brain diseases. However, previous registration methods don't take advantage of the prior knowledge of bilateral brain symmetry. Moreover, the difference in gray scale information of different modal images increases the difficulty of registration. In this paper, a multimodal medical image registration method based on image segmentation and symmetric self-similarity is proposed. This method uses modal independent self-similar information and modal consistency information to register images. More particularly, we propose two novel symmetric self-similarity constraint operators to constrain the segmented medical images and convert each modal medical image into a unified modal for multimodal image registration. The experimental results show that the proposed method can effectively reduce the error rate of brain MR multimodal medical image registration with rotation and translation transformations (average 0.43mm and 0.60mm) respectively, whose accuracy is better compared to state-of-the-art image registration methods.

Image Segmentation Using Color Morphological Pyramids (Color Morphological Pyramids를 이용한 이미지 분할)

  • 이석기;최은희;김석태
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.5
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    • pp.789-795
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    • 2002
  • Color image is formed of combination of three color channels. Therefore its architecture is very complicated and it requires complicated image Processing for effective image segmentation. In this paper. we propose architecture of universalized Color Morphological Pyramids(CMP) which is able to give effective image segmentation. Image Pyramid architecture is a successive Image sequence whose area ratio $2^{\int}({\int}=1,2,....,N)$ after filtering and subsampling of input image. In this technique, noise removed by sequential filtering and resolution is degraded by downsampling using CMP in various color spaces. After that, new level images are constructed that apply formula using distance of neighbor vectors in close level images and segments its image. The feasibility of proposed method is examined by comparing with the results obtained from the existing method.