• Title/Summary/Keyword: 이미지 회전

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A study for efficient image use in the mobile contents development (모바일 컨텐츠 제작을 위한 효율적인 이미지 활용에 대한 연구)

  • Kim, Jeong-Hoon
    • Journal of Korea Game Society
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    • v.5 no.1
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    • pp.53-60
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    • 2005
  • To produce deep, entertaining mobile content, a large number of images must be included. But because of the limits on runtime memory for mobile phones, images cannot be used as easily in a mobile environment as they are in a computer. Therefore in this paper, I propose several different methods for efficiently using images in a mobile environment. The various methods I propose for using images are: Creating images using compression/decompression and rotation/symmetry Creating images of several different colors by changing the palette index of a bitmap Creating images through image combination Creating background images by using tile maps Creating new images through effects.

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Machine Learning Data Extension Way for Confirming Genuine of Trademark Image which is Rotated (회전한 상표 이미지의 진위 결정을 위한 기계 학습 데이터 확장 방법)

  • Gu, Bongen
    • Journal of Platform Technology
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    • v.8 no.1
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    • pp.16-23
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    • 2020
  • For protecting copyright for trademark, convolutional neural network can be used to confirm genuine of trademark image. For this, repeated training one trademark image degrades the performance of machine learning because of overfitting problem. Therefore, this type of machine learning application generates training data in various way. But if genuine trademark image is rotated, this image is classified as not genuine trademark. In this paper, we propose the way for extending training data to confirm genuine of trademark image which is rotated. Our proposed way generates rotated image from genuine trademark image as training data. To show effectiveness of our proposed way, we use CNN machine learning model, and evaluate the accuracy with test image. From evaluation result, our way can be used to generate training data for machine learning application which confirms genuine of rotated trademark image.

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Efficient Rotation-Invariant Boundary Image Matching Using the Envelope-based Lower Bound (엔빌로프 기반 하한을 사용한 효율적인 회전-불변 윤곽선 이미지 매칭)

  • Kim, Sang-Pil;Moon, Yang-Sae;Hong, Sun-Kyong
    • The KIPS Transactions:PartD
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    • v.18D no.1
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    • pp.9-22
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    • 2011
  • In this paper we present an efficient solution to rotation?invariant boundary image matching. Computing the rotation-invariant distance between image time-series is a time-consuming process since it requires a lot of Euclidean distance computations for all possible rotations. In this paper we propose a novel solution that significantly reduces the number of distance computations using the envelope-based lower bound. To this end, we first present how to construct a single envelope from a query sequence and how to obtain a lower bound of the rotation-invariant distance using the envelope. We then show that the single envelope-based lower bound can reduce a number of distance computations. This approach, however, may cause bad performance since it may incur a larger lower bound by considering all possible rotated sequences in a single envelope. To solve this problem, we present a concept of rotation interval, and using the rotation interval we generalize the envelope-based lower bound by exploiting multiple envelopes rather than a single envelope. We also propose equi-width and envelope minimization divisions as the method of determining rotation intervals in the multiple envelope approach. Experimental results show that our envelope-based solutions outperform existing solutions by one or two orders of magnitude.

Analysis of performance changes based on the characteristics of input image data in the deep learning-based algal detection model (딥러닝 기반 조류 탐지 모형의 입력 이미지 자료 특성에 따른 성능 변화 분석)

  • Juneoh Kim;Jiwon Baek;Jongrack Kim;Jungsu Park
    • Journal of Wetlands Research
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    • v.25 no.4
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    • pp.267-273
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    • 2023
  • Algae are an important component of the ecosystem. However, the excessive growth of cyanobacteria has various harmful effects on river environments, and diatoms affect the management of water supply processes. Algal monitoring is essential for sustainable and efficient algae management. In this study, an object detection model was developed that detects and classifies images of four types of harmful cyanobacteria used for the criteria of the algae alert system, and one diatom, Synedra sp.. You Only Look Once(YOLO) v8, the latest version of the YOLO model, was used for the development of the model. The mean average precision (mAP) of the base model was analyzed as 64.4. Five models were created to increase the diversity of the input images used for model training by performing rotation, magnification, and reduction of original images. Changes in model performance were compared according to the composition of the input images. As a result of the analysis, the model that applied rotation, magnification, and reduction showed the best performance with mAP 86.5. The mAP of the model that only used image rotation, combined rotation and magnification, and combined image rotation and reduction were analyzed as 85.3, 82.3, and 83.8, respectively.

The Method of Optical Stimulus by Reticle for pH Image Detection using LAPS (LAPS를 위한 pH 이미지 검출용 격자무늬 광자극 방법)

  • Bae, S.K.;Kang, S.W.;Cho, J.H.
    • Journal of Sensor Science and Technology
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    • v.10 no.6
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    • pp.317-327
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    • 2001
  • In this paper, we proposed a new detection method of pH image to effectively measure a 2-dimensional pH distribution of test materials by irradiating an frequency modulated light to LAPS using a reticle. It could measure simultaneously signals in one line by applying a modulated light having difference frequency for each pixel using a frequency modulating reticle, and calculating an amplitude with respect to a frequency component by the light source. To experiment the proposed method, we designed and implemented a reticle considering of a LAPS's characteristic, and reconstructed an image by frequency analysis using the implemented reticle and test pattern image. As a result, we verified that the proposed method using the reticle was able to detect 30 times faster for a $30{\times}30$ pixels pH image having a PSNR of 22-24 [dB] than conventional method.

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Comparison of Deep Learning Models for Judging Business Card Image Rotation (명함 이미지 회전 판단을 위한 딥러닝 모델 비교)

  • Ji-Hoon, Kyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.27 no.1
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    • pp.34-40
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    • 2023
  • A smart business card printing system that automatically prints business cards requested by customers online is being activated. What matters is that the business card submitted by the customer to the system may be abnormal. This paper deals with the problem of determining whether the image of a business card has been abnormally rotated by adopting artificial intelligence technology. It is assumed that the business card rotates 0 degrees, 90 degrees, 180 degrees, and 270 degrees. Experiments were conducted by applying existing VGG, ResNet, and DenseNet artificial neural networks without designing special artificial neural networks, and they were able to distinguish image rotation with an accuracy of about 97%. DenseNet161 showed 97.9% accuracy and ResNet34 also showed 97.2% precision. This illustrates that if the problem is simple, it can produce sufficiently good results even if the neural network is not a complex one.

Creation of Fractal Images with Rotational Symmetry Based on Julia Set (Julia Set을 이용한 회전 대칭 프랙탈 이미지 생성)

  • Han, Yeong-Deok
    • Journal of Korea Game Society
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    • v.14 no.6
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    • pp.109-118
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    • 2014
  • We studied the creation of fractal images with polygonal rotation symmetry. As in Loocke's method[13] we start with IFS of affine functions that create polygonal fractals and extends the IFS by adding functions that create Julia sets instead of adding square root functions. The resulting images are rotationally symmetric and Julia set shaped. Also we can improve fractal images by modifying probabilistic IFS algorithm, and we suggest a method of deforming Julia set by changing exponent value.

A study on Robust Feature Image for Texture Classification and Detection (텍스쳐 분류 및 검출을 위한 강인한 특징이미지에 관한 연구)

  • Kim, Young-Sub;Ahn, Jong-Young;Kim, Sang-Bum;Hur, Kang-In
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.10 no.5
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    • pp.133-138
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    • 2010
  • In this paper, we make up a feature image including spatial properties and statistical properties on image, and format covariance matrices using region variance magnitudes. By using it to texture classification, this paper puts a proposal for tough texture classification way to illumination, noise and rotation. Also we offer a way to minimalize performance time of texture classification using integral image expressing middle image for fast calculation of region sum. To estimate performance evaluation of proposed way, this paper use a Brodatz texture image, and so conduct a noise addition and histogram specification and create rotation image. And then we conduct an experiment and get better performance over 96%.

A Study on the Shape Feature Extraction for Content-based Image Retrieval System (내용기반 이미지 검색시스템을 위한 형태 정보 추출에 관한 연구)

  • 윤후병;황호전;서정원;두길수;이신원;정성종;안동언
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10b
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    • pp.265-267
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    • 1998
  • 본 논문은 내용기반 이미지 검색시스템에서 사용하는 특징벡터들 중에서 하나인 형태 특징벡터를 추출하는데 초점을 맞쳤다. 특히 다양한 방향으로 회전된 영상의 형태를 수용할 수 있는 모멘트 정보를 영상의 형태 특징벡터로 사용하였다. 그 결과 영상과 회전되지 않은 영상간의 차이값이 0에 가까워 유사성이 아주 좋음을 알 수 있었다.

Efficient and Detailed Texture Synthesis with Orientation Considerations (방향을 고려한 효율적이고 디테일한 텍스처 합성)

  • Yeon Hee Choo;Jong-Hyun Kim
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.575-576
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    • 2023
  • 본 논문에서는 텍스처 합성할 때 방향을 고려하여 합성의 품질의 개선시킬 수 있는 방법을 제안한다. 또한 고정된 회전 각도가 아닌, 다양한 각도를 자동으로 샘플링하여 효율적으로 예제 이미지를 생성할 수 있도록 하였고, 이를 통해 합성 경계간의 차이를 자연스럽게 완화시킬 수 있는 결과를 실험을 통해 보여준다.

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