• Title/Summary/Keyword: Grayscale Value

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A Data Hiding Scheme for Grayscale Images Using a Square Function

  • Kwon, Hyejin;Kim, Haemun;Kim, Soonja
    • Journal of Korea Multimedia Society
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    • v.17 no.4
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    • pp.466-477
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    • 2014
  • Many image hiding schemes based on least significant bit (LSB) transformation have been proposed. One of the LSB-based image hiding schemes that employs diamond encoding was proposed in 2008. In this scheme, the binary secret data is converted into base n representation, and the converted secret data is concealed in the cover image. Here, we show that this scheme has two vulnerabilities: noticeable spots in the stego-image, i.e., a non-smooth embedding result, and inefficiency caused by rough re-adjustment of falling-off-boundary value and impractical base translation. Moreover, we propose a new scheme that is efficient and produces a smooth and high quality embedding result by restricting n to power of 2 and using a sophisticated re-adjustment procedure. Our experimental results show that our scheme yields high quality stego-images and is secure against RS detection attack.

Information Hiding Method based on Interpolation using Max Difference of RGB Pixel for Color Images (컬러 영상의 RGB 화소 최대차분 기반 보간법을 이용한 정보은닉 기법)

  • Lee, Joon-Ho;Kim, Pyung-Han;Jung, Ki-Hyun;Yoo, Kee-Young
    • Journal of Korea Multimedia Society
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    • v.20 no.4
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    • pp.629-639
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    • 2017
  • Interpolation based information hiding methods are widely used to get information security. Conventional interpolation methods use the neighboring pixel value and simple calculation like average to embed secret bit stream into the image. But these information hiding methods are not appropriate to color images like military images because the characteristics of military images are not considered and these methods are restricted in grayscale images. In this paper, the new information hiding method based on interpolation using RGB pixel values of color image is proposed and the effectiveness is analyzed through experiments.

Consideration of Image Quality of Dithered Picture by Constrained Average Method Using Various Probability Distribution Models

  • Sato, Mitsuhiro;Hasegawa, Madoka;Kato, Shigeo
    • Proceedings of the IEEK Conference
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    • 2002.07c
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    • pp.1495-1498
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    • 2002
  • The constrained average method is one of dither methods which combines edge emphasis and grayscale rendition to provide legibility of textual region and proper quality of continuous tone region. How-ever, image quality of continuous tone region is insufficient compared to other dither methods, such as ordered dither methods or the error diffusion method. The constrained average method uses a uniform distribution function to decide number of lit pixels related to the average intensity in a picture area. However, actual distribution of continuous tone region is closer to the Laplacian distribution or triangle distribution. In this paper, we introduce various probability distributions and the actual luminance distribution to decide the threshold value of the constrained average method in order to improve image quality of dithered image.

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A Study on the Luster of Commercially Available Fabrics -Analysis of Images Acquired at Various Observing Angles- (직물광택의 변각촬영 이미지에 대한 분석적 연구)

  • 신경인;김종준
    • Journal of the Korean Society of Clothing and Textiles
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    • v.26 no.8
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    • pp.1117-1127
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    • 2002
  • This paper is on the luster property of fertile fabric materials which is one of the important factors related to the development of clothing materials leading to the value-added products. Using several image analysis techniques, the optical properties, especially luster related ones, of the commercially available fabrics were measured and analyzed. The fabric samples included 6 kinds of preliminary experimental fabrics along with 22 kinds of fabric which were commercially available. The images acquired at various observing angles are taken by 44 Points and these Pictures are analyzed into luster through the image analysis program. The preliminary experiment demonstrated the effects of weave types and the number of yarn twist on the luster of the fabrics through the use of the image analysis program.

Medical Diagnosis Algorithm Based on Tongue Image on Mobile Device

  • Zhou, Zibo;Peng, Dongliang;Gao, Fumeng;Leng, Lu
    • Journal of Multimedia Information System
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    • v.6 no.2
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    • pp.99-106
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    • 2019
  • In traditional Chinese medical (TCM) science, tongue images can be observed for medical diagnosis; however, the tongue diagnosis of TCM is influenced by the subjective factors of doctors, and the diagnosis results vary from person to person. Quantitative TCM tongue diagnosis can improve the accuracy of diagnosis and increase the application value. In this paper, digital image processing and pattern recognition technologies are employed on mobile device to classify tongue images collected in different health states. First, through grayscale integral projection processing, the trough is found to localize the tongue body. Then the tongue body image is transferred from RGB color space to HSV color space, and the average H and S values are considered as the color features. Finally, the diagnosis results are obtained according to the relationship between the color characteristics and physical symptoms.

Image Steganography to Hide Unlimited Secret Text Size

  • Almazaydeh, Wa'el Ibrahim A.
    • International Journal of Computer Science & Network Security
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    • v.22 no.4
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    • pp.73-82
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    • 2022
  • This paper shows the hiding process of unlimited secret text size in an image using three methods: the first method is the traditional method in steganography that based on the concealing the binary value of the text using the least significant bits method, the second method is a new method to hide the data in an image based on Exclusive OR process and the third one is a new method for hiding the binary data of the text into an image (that may be grayscale or RGB images) using Exclusive and Huffman Coding. The new methods shows the hiding process of unlimited text size (data) in an image. Peak Signal to Noise Ratio (PSNR) is applied in the research to simulate the results.

A Shadow Region Suppression Method using Intensity Projection and Converting Energy to Improve the Performance of Probabilistic Background Subtraction (확률기반 배경제거 기법의 향상을 위한 밝기 사영 및 변환에너지 기반 그림자 영역 제거 방법)

  • Hwang, Soon-Min;Kang, Dong-Joong
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.1
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    • pp.69-76
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    • 2010
  • The segmentation of moving object in video sequence is a core technique of intelligent image processing system such as video surveillance, traffic monitoring and human tracking. A typical method to segment a moving region from the background is the background subtraction. The steps of background subtraction involve calculating a reference image, subtracting new frame from reference image and then thresholding the subtracted result. One of famous background modeling is Gaussian mixture model (GMM). Even though the method is known efficient and exact, GMM suffers from a problem that includes false pixels in ROI (region of interest), specifically shadow pixels. These false pixels cause fail of the post-processing tasks such as tracking and object recognition. This paper presents a method for removing false pixels included in ROT. First, we subdivide a ROI by using shape characteristics of detected objects. Then, a method is proposed to classify pixels from using histogram characteristic and comparing difference of energy that converts the color value of pixel into grayscale value, in order to estimate whether the pixels belong to moving object area or shadow area. The method is applied to real video sequence and the performance is verified.

Multispectral X-ray imaging to distinguish among dental materials

  • Peter, Ann-Christin;Schnaubelt, Matthias;Gente, Michael
    • Imaging Science in Dentistry
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    • v.47 no.4
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    • pp.247-254
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    • 2017
  • Purpose: Dual-energy X-ray imaging is widely used today in various areas of medicine and in other applications. However, no similar technique exists for dental applications. In this study, we propose a dual-energy technique for dental diagnoses based on voltage-switching. Materials and Methods: The method presented in this study allowed different groups of materials to be classified based on atomic number, thereby enabling two-dimensional images to be colorized. Computer simulations showed the feasibility of this approach. Using a number of different samples with typical biologic and synthetic dental materials, the technique was applied to radiographs acquired with a commercially available dental X-ray unit. Results: This technique provided a novel visual representation of the intraoral environment in three colors, and is of diagnostic value when compared to state-of-the-art grayscale images, since the oral cavity often contains multiple permanent foreign materials. Conclusion: This work developed a technique for two-dimensional dual-energy imaging in the context of dental applications and showed its feasibility with a commercial dental X-ray unit in simulation and experimental studies.

3D Segmentation for High-Resolution Image Datasets Using a Commercial Editing Tool in the IoT Environment

  • Kwon, Koojoo;Shin, Byeong-Seok
    • Journal of Information Processing Systems
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    • v.13 no.5
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    • pp.1126-1134
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    • 2017
  • A variety of medical service applications in the field of the Internet of Things (IoT) are being studied. Segmentation is important to identify meaningful regions in images and is also required in 3D images. Previous methods have been based on gray value and shape. The Visible Korean dataset consists of serially sectioned high-resolution color images. Unlike computed tomography or magnetic resonance images, automatic segmentation of color images is difficult because detecting an object's boundaries in colored images is very difficult compared to grayscale images. Therefore, skilled anatomists usually segment color images manually or semi-automatically. We present an out-of-core 3D segmentation method for large-scale image datasets. Our method can segment significant regions in the coronal and sagittal planes, as well as the axial plane, to produce a 3D image. Our system verifies the result interactively with a multi-planar reconstruction view and a 3D view. Our system can be used to train unskilled anatomists and medical students. It is also possible for a skilled anatomist to segment an image remotely since it is difficult to transfer such large amounts of data.

A Road Luminance Measurement Application based on Android (안드로이드 기반의 도로 밝기 측정 어플리케이션 구현)

  • Choi, Young-Hwan;Kim, Hongrae;Hong, Min
    • Journal of Internet Computing and Services
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    • v.16 no.2
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    • pp.49-55
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    • 2015
  • According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.