• 제목/요약/키워드: Drawing Image

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Interactive drawing with user's intentions using image segmentation

  • Lim, Sooyeon
    • International Journal of Internet, Broadcasting and Communication
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    • 제10권3호
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    • pp.73-80
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    • 2018
  • This study introduces an interactive drawing system, a tool that allows user to sketch and draw with his own intentions. The proposed system enables the user to express more creatively through a tool that allows the user to reproduce his original idea as a drawing and transform it using his body. The user can actively participate in the production of the artwork by studying the unique formative language of the spectator. In addition, the user is given an opportunity to experience a creative process by transforming arbitrary drawing into various shapes according to his gestures. Interactive drawing systems use the segmentation of the drawing image as a way to extend the user's initial drawing idea. The system includes transforming a two-dimensional drawing into a volume-like form such as a three-dimensional drawing using image segmentation. In this process, a psychological space is created that can stimulate the imagination of the user and project the object of desire. This process of drawing personification plays a role of giving the user familiarity with the artwork and indirectly expressing his her emotions to others. This means that the interactive drawing, which has changed to the emotional concept of interaction beyond the concept of information transfer, can create a cooperative sensation image between user's time and space and occupy an important position in multimedia society.

심상그리기가 좌편 무시현상에 미치는 영향: 사례연구 (The Effects of a Mental Image Drawing on Left Neglect: a Case Study)

  • 김하경;황영진;정옥란
    • 음성과학
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    • 제12권3호
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    • pp.91-102
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    • 2005
  • This study investigated to the effects of a mental image drawing in RHD patients with left neglect. Three subjects participated in this study. All subjects were right handed and native speaker of korean. In task 1, the patients were presented with visual stimulus card directly above the response sheet and were asked to draw the picture. In task 2, they were presented with items auditorily and asked to draw the picture(mental image drawing). In all experimental conditions, there was no response time limit. The results showed that the subjects showed left neglect leaving some space on the left side in task 1. And the picture was drawn the left side from the right in direction. However, the neglect disappeared in task 2. And the picture was drawn the right side from the left in direction. The results of the present study suggested that a mental image drawing technique can be effective in treating individuals who exhibit left neglect. Also, the picture direction showed that the korean normality was same.

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Deep Learning Similarity-based 1:1 Matching Method for Real Product Image and Drawing Image

  • Han, Gi-Tae
    • 한국컴퓨터정보학회논문지
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    • 제27권12호
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    • pp.59-68
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    • 2022
  • 본 논문은 주어진 현품 영상과 도면 영상의 유사도를 비교하여 1:1 검증을 위한 방법을 제시한 것으로, CNN(Convolutional Neural Network) 기반의 딥러닝 모델을 두 개로 결합하여 Siamese Net을 구성하고 현품 영상과 도면 영상(정면도, 좌우 측면도, 평면도 등)을 같은 제품이면 1로 다른 제품이면 0으로 학습하며, 추론은 현품 영상과 도면 영상을 쌍으로 질의하여 해당 쌍이 같은 제품인지 아닌지를 판별하는 딥러닝 모델을 제안한다. 현품 영상과 도면 영상과의 유사도가 문턱 값(Threshold: 0.5) 이상이면 동일한 제품이고, 문턱 값 미만이면 다른 제품이라고 판별한다. 본 연구에서는 질의 쌍으로 동일제품의 현품 영상과 도면 영상이 주어졌을 때(긍정 : 긍정) "동일제품"으로 판별할 정확도는 약 71.8%로 나타났고, 질의 쌍으로 다른 현품 영상과 도면 영상이 주어졌을 때(긍정: 부정) "다른제품"으로 판별할 정확도는 약 83.1%를 나타내었다. 향후 제안한 모델에 파라미터 최적화 연구를 접목하고 데이터 정제 등의 과정을 추가하여 현품 영상과 도면 영상의 매칭 정확도를 높이는 연구를 진행할 예정이다.

Near-infrared Spectroscopy and an Example of HAM Study;Brain Activation in the Development of Drawing Skills

  • Kobayashi, Harumi;Yasuda, Tetsuya;Suzuki, Satoshi;Takase, Hiroki
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.1745-1748
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    • 2005
  • Near-infrared spectroscopy (NIRS) can be used to monitor brain activation by measuring changes in the concentration of oxy- and deoxy-hemoglobin (Hb) by their different spectra in the near-infrared range. Because NIRS is a noninvasive, highly flexible and portable device, it is very suitable to study brain activation when a human repeatedly performs a manipulative task, and possibly provides useful information to construct human adaptive mechatronics (HAM). There is some evidence that the dorsolateral prefrontal cortex (DLPFC) plays a major role in working memory and it is proposed that the use of working memory decreases as a human develops manipulative skills. In the present study, we investigated the activation of the dorsolateral prefrontal cortex (DLPFC) of the brain in Brodmann's areas 9 and 46 in drawing tasks to examine whether NIRS can measure the changes of DLPFC activation as a human develops manipulative skills. Subjects performed a mirror image drawing task and a square drawing task by ones' left hands. In the mirror image task the subject drew following a star shape based on a mirror image of it, but square drawing did not involve mirror image and was estimated to be simpler. The changes of the concentration of oxy-Hb was higher in the mirror image drawing than the square drawing in most subjects. The changes of oxy-Hb decreased as the subject repeated the drawing task in most subjects. In conclusion, The activation of DLPFC measured by NIRS can reflect the brain activity in the development of manipulative skills.

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텐서 기반 스트로크 생성에 의한 펜화기법 (A Pen Drawing Method by Tensor-based Strokes Generation)

  • 신도경;안은영
    • 한국멀티미디어학회논문지
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    • 제20권4호
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    • pp.713-720
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    • 2017
  • We present a non-photo realistic pen-ink drawing method for outlining and shading of the input image. Especially, we focus on the detailed illustration of the image of which stroke's direction is important. The pen-ink renderer is an alternative display models user can generate traditional illustration renderings of their photo realistic image. The previously proposed pen drawing methods produce feasible description in general image but it is difficult to express in detail for the sophisticated images that need to consider the direction of stroke for each image region. In order to overcome the disadvantages of the conventional method, a direction vector is extracted from a tensor field and we determine a stroke's direction in consideration of not only an edge area but also a gradient of a surrounding area in the image. For more detailed description for the sophisticated image, we generate white noises based on the light and shade of the input image and determine the direction and length of the stroke by using the tensor field for each generated white noise. The proposed method works particularly well for traditional architectural images where the direction and detailed description of the pen is important.

인공지능기법을 이용한 동적 이미지 도면 부품정보 인식에 관한 연구 (A Study on the Dynamic Image Drawing Part Information Recognition using Artificial Intelligence)

  • 이주상;강성인;이상배
    • 한국지능시스템학회논문지
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    • 제16권4호
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    • pp.449-453
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    • 2006
  • 본 논문은 시설물의 효율적인 유지보수 관리를 위해 이미지 도면의 부품정보를 효율적으로 활용할 수 있는 방안을 제시한다. 시설물 설계 도면에는 시설물을 구성하는 부품에 대한 정보가 표현되어 있고, 각 부품을 구분하기 위해 레전드 문자가 표기되어 있다. 본 논문은 이미지 도면의 레전드 문자 인식을 위해 인공지능 기법을 적용한다. 마지막으로, 본 논문에서 제안한 방법의 효율성을 평가하기 위해 인공지능기법을 도면관리시스템에 적용한다.

다양한 선 두께들을 인식하고 그리는 로봇 팔 (Robot Arm Recognizing and Drawing Various Line Thicknesses)

  • 조원서;김동한;류근호
    • 제어로봇시스템학회논문지
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    • 제19권12호
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    • pp.1105-1110
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    • 2013
  • In this paper, a robot arm capable of recognizing and drawing various line thicknesses is developed. Conventional line drawing robots are not capable of adjusting the thickness of lines. However, to draw faster and to enrich the expression of line drawing robots, it is necessary to adjust line thickness using a brush pen. Simple images are acquired and various line thicknesses are recognized by image processing. Trajectories of lines are generated with distance sorting using thinning and corner point detections for each label. Information on line thickness and trajectory is sent to the controller of a robot arm taking into consideration 2D inverse kinematics. Through this process, the robot arm can draw various lines thicknesses along 2D trajectories with 3 motors. Robot arm for detailed drawing will be studied in the future.

Sketch-based 3D modeling by aligning outlines of an image

  • Li, Chunxiao;Lee, Hyowon;Zhang, Dongliang;Jiang, Hao
    • Journal of Computational Design and Engineering
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    • 제3권3호
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    • pp.286-294
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    • 2016
  • In this paper we present an efficient technique for sketch-based 3D modeling using automatically extracted image features. Creating a 3D model often requires a drawing of irregular shapes composed of curved lines as a starting point but it is difficult to hand-draw such lines without introducing awkward bumps and edges along the lines. We propose an automatic alignment of a user's hand-drawn sketch lines to the contour lines of an image, facilitating a considerable level of ease with which the user can carelessly continue sketching while the system intelligently snaps the sketch lines to a background image contour, no longer requiring the strenuous effort and stress of trying to make a perfect line during the modeling task. This interactive technique seamlessly combines the efficiency and perception of the human user with the accuracy of computational power, applied to the domain of 3D modeling where the utmost precision of on-screen drawing has been one of the hurdles of the task hitherto considered a job requiring a highly skilled and careful manipulation by the user. We provide several examples to demonstrate the accuracy and efficiency of the method with which complex shapes were achieved easily and quickly in the interactive outline drawing task.

영상 특징 정합 및 양선형 보간법을 이용한 자동 도면 정합 검사 시스템 (Automatic Drawing Conformity Inspection System Using Image Features Matching and Bilinear Interpolation)

  • 송복득;이승희;정맹금;김혜진;신범주;이완직;양황규;김명호
    • 한국전기전자재료학회논문지
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    • 제25권4호
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    • pp.321-327
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    • 2012
  • To evaluate whether or not their product is in conformity with its drawing, today's factories manufacturing rubber and/or plastic products use manual process. In manual conformity inspection process, a person decides conformity as comparing drawing to image of product with his eyes. The manual process is tedious and time-consuming in addition that it is impossible to automatically record various informations related to inspection. To solve such problems, this paper proposes automatic drawing conformity inspection system based on computer vision technologies such as image feature matching and bilinear interpolation. The test results show that proposed system is a lot faster when comparing with manual system.