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LSB Image Steganography Based on Blocks Matrix Determinant Method

  • Shehzad, Danish;Dag, Tamer
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권7호
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    • pp.3778-3793
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    • 2019
  • Image steganography is one of the key types of steganography where a message to be sent is hidden inside the cover image. The most commonly used techniques for image steganography rely on LSB steganography. In this paper, a novel image steganography technique based on blocks matrix determinant method is proposed. Under this method, a cover image is divided into blocks of size $2{\times}2$ pixels and the determinant of each block is calculated. The comparison of the determinant values and corresponding data bits yields a delicate way for the embedment of data bits. The main aim of the proposed technique is to ensure concealment of secret data inside an image without affecting the cover image quality. When the proposed steganography method is compared with other existing LSB steganography methods, it is observed that it not only provides higher PSNR, lower MSE but also guarantees better quality of the stego image.

An image enhancement Method for extracting multi-license plate region

  • Yun, Jong-Ho;Choi, Myung-Ryul;Lee, Sang-Sun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권6호
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    • pp.3188-3207
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    • 2017
  • In this paper, we propose an image enhancement algorithm to improve license plate extraction rate in various environments (Day Street, Night Street, Underground parking lot, etc.). The proposed algorithm is composed of image enhancement algorithm and license plate extraction algorithm. The image enhancement method can improve an image quality of the degraded image, which utilizes a histogram information and overall gray level distribution of an image. The proposed algorithm employs an interpolated probability distribution value (PDV) in order to control a sudden change in image brightness. Probability distribution value can be calculated using cumulative distribution function (CDF) and probability density function (PDF) of the captured image, whose values are achieved by brightness distribution of the captured image. Also, by adjusting the image enhancement factor of each part region based on image pixel information, it provides a function that can adjust the gradation of the image in more details. This processed gray image is converted into a binary image, which fuses narrow breaks and long thin gulfs, eliminates small holes, and fills gaps in the contour by using morphology operations. Then license plate region is detected based on aspect ratio and license plate size of the bound box drawn on connected license plate areas. The images have been captured by using a video camera or a personal image recorder installed in front of the cars. The captured images have included several license plates on multilane roads. Simulation has been executed using OpenCV and MATLAB. The results show that the extraction success rate is more improved than the conventional algorithms.

기업이미지에 대한 환경친화적 CI 비쥬얼 디자인의 효과 (The Effect of Green-oriented CI Visual Design on Corporate Image)

  • 나광진;박혜상;권민택
    • 감성과학
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    • 제11권3호
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    • pp.339-356
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    • 2008
  • The purpose of this research was to identify the difference between expected and actual corporate image in the market and to verify the possibility of green-oriented corporate identity (CI) visual design as a useful method for communicating with consumers. In addition, this research suggests how green-oriented CI visual design can effectively convey corporate image to consumers. The methods of research used to achieve this aim were case studies and questionnaire surveys. In regard to the results, the difference between consumers'perceived favourable corporate image and companies' expectation about corporate image was found. Moreover, the results show that green-oriented visual identity (VI) design can improve corporate image. In turn, the gap between the expected and actual perception of corporate image can be decreased through green-oriented design. Based on these results, a method of effective development for green-oriented VI design is recommended.

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Reduction of the Temporal Bright-Image Sticking in AC-PDP Modules Using the Vacuum Sealing Method

  • Park, Choon-Sang;Cho, Byung-Gwon;Tae, Heung-Sik
    • Journal of Information Display
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    • 제9권4호
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    • pp.39-44
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    • 2008
  • This paper investigates the effects of the existing sealing methods, such as the conventional atmospheric-pressure sealing method and vacuum sealing, on temporal bright-image sticking. To produce a residual image caused by temporal brightimage sticking, the entire region of a 42-in panel with an Xe-(11%)-He(35%) gas mixture was abruptly changed to a full-white background image after displaying a square-type image at peak luminance for about 60s. From the monitoring of the difference in the display luminance, infrared emission, color temperature, and disappearing time between the cells with and without temporal bright-image sticking, it was observed that the vacuum sealing method contributes to the reduction of temporal bright-image sticking.

Development of Pattern Classifying System for cDNA-Chip Image Data Analysis

  • Kim, Dae-Wook;Park, Chang-Hyun;Sim, Kwee-Bo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.838-841
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    • 2005
  • DNA Chip is able to show DNA-Data that includes diseases of sample to User by using complementary characters of DNA. So this paper studied Neural Network algorithm for Image data processing of DNA-chip. DNA chip outputs image data of colors and intensities of lights when some sample DNA is putted on DNA-chip, and we can classify pattern of these image data on user pc environment through artificial neural network and some of image processing algorithms. Ultimate aim is developing of pattern classifying algorithm, simulating this algorithm and so getting information of one's diseases through applying this algorithm. Namely, this paper study artificial neural network algorithm for classifying pattern of image data that is obtained from DNA-chip. And, by using histogram, gradient edge, ANN and learning algorithm, we can analyze and classifying pattern of this DNA-chip image data. so we are able to monitor, and simulating this algorithm.

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고전영화복원 사례를 통한 한국형영상복원 소프트웨어 개발 필요성에 관한 연구 (A Study on needs of Software Development for Korean Image Restoration through Cases of Classical Film Restoration)

  • 김치용;한명희;김종찬
    • 한국멀티미디어학회논문지
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    • 제17권12호
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    • pp.1528-1536
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    • 2014
  • Although the process about korea image restoration contents program development and liberalization have cultural and artistic worth, it is not possible to restore technically or cost enormous expense. In the study, it suggest the needs of korea image restoration contents program development through image restoration case. It is revitalize that the study in digital image restoration technical prepare the ground for passing high-qualities cultural legacy by restoring classical film. We think the development of korea image restoration software will strengthen the basis to the new creation industry of high value-added in the global cultural prosperity industry.

A REVERSIBLE IMAGE AUTHENTICATION METHOD FREE FROM LOCATION MAP AND PARAMETER MEMORIZATION

  • Han, Seung-Wu;Fujiyoshi, Masaaki;Kiya, Hitoshi
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2009년도 IWAIT
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    • pp.572-577
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    • 2009
  • This paper proposes a novel reversible image authentication method that requires neither location map nor memorization of parameters. The proposed method detects image tampering and further localizes tampered regions. Though this method once distorts an image to hide data for tamper detection, it recovers the original image from the distorted image unless no tamper is applied to the image. The method extracts hidden data and recovers the original image without memorization of any location map that indicates hiding places and of any parameter used in the algorithm. This feature makes the proposed method practical. Simulation results show the effectiveness of the proposed method.

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Enhancement of Color Images with Blue Sky Using Different Method for Sky and Non-Sky Regions

  • Ghimire, Deepak;Pant, Suresh Raj;Lee, Joonwhoan
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2013년도 춘계학술발표대회
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    • pp.215-218
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    • 2013
  • In this paper, we proposed a method for enhancement of color images with sky regions. The input image is converted into HSV space and then sky and non-sky regions are separated. For sky region, saturation enhancement is performed for each pixel based on the enhancement factor calculated from the average saturation of its local neighborhood. On the other hand, for the non-sky region, the enhancement is applied only on the luminance value (V) component of the HSV color image, which is performed in two steps. The luminance enhancement, which is also called as dynamic range compression, is carried out using nonlinear transfer function. Again, each pixel is further enhanced for the adjustment of the image contrast depending upon the center pixel and its neighborhood pixel values. At last, the original H and V component image and enhanced S component image for the sky region, and original H and S component image and enhanced V component image for the non-sky region are converted back to RGB image.

A Survey on Image Emotion Recognition

  • Zhao, Guangzhe;Yang, Hanting;Tu, Bing;Zhang, Lei
    • Journal of Information Processing Systems
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    • 제17권6호
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    • pp.1138-1156
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    • 2021
  • Emotional semantics are the highest level of semantics that can be extracted from an image. Constructing a system that can automatically recognize the emotional semantics from images will be significant for marketing, smart healthcare, and deep human-computer interaction. To understand the direction of image emotion recognition as well as the general research methods, we summarize the current development trends and shed light on potential future research. The primary contributions of this paper are as follows. We investigate the color, texture, shape and contour features used for emotional semantics extraction. We establish two models that map images into emotional space and introduce in detail the various processes in the image emotional semantic recognition framework. We also discuss important datasets and useful applications in the field such as garment image and image retrieval. We conclude with a brief discussion about future research trends.

변환학습을 이용한 장면 분류 (The Combined Effect and Therapeutic Effects of Color)

  • 신성윤;신광성;남수태
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 춘계학술대회
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    • pp.338-339
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    • 2021
  • 본 논문에서는 변환 학습을 기반으로 한 다중 클래스 이미지 장면 분류 방법을 제안한다. 이미지 분류를 위해 대형 이미지 데이터 세트 ImageNet에 대해 사전 학습 한 ResNet (ResNet) 모델을 사용하는 방법이다. CNN 모델의 이미지 분류 방법에 비해 분류 정확도 및 효율성을 크게 향상시킬 수 있다.

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