• Title/Summary/Keyword: RGB filtering

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A Study on the Augmented Reality Display for Educating Power Tiller Operator using Chroma-key (크로마키를 이용한 증강현실 영상출력 연구)

  • Kim, Yu Yong;Noh, Jae Seung;Hong, Sun Jung
    • Journal of agriculture & life science
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    • v.51 no.1
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    • pp.205-212
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    • 2017
  • This study aimed to output augmented reality display using chroma-key so that power tiller simulator can be operated smoothly while wearing the head mounted display. In this paper, we propose a chroma-eliminating image filtering method. Experimental results show that the maximum and minimum values of hue, saturation and intensity were 0.52, 0.153, 0.57, 0.16, 1, and 0.12, respectively. A keypad was used to set the initial position of augmented reality adjusted with the front, back, top, bottom, left, and right buttons. The initial position value is always maintained and managed according to the trailer attachment and detachment. Finally, we show that the augmented reality merged with virtual image and the acquired image of operation device using coordinate values obtained from the HMD and the position tracking sensor as relative coordinates in Unity program that is the ultimate game development platform.

An adaptive watermarking for remote sensing images based on maximum entropy and discrete wavelet transformation

  • Yang Hua;Xu Xi;Chengyi Qu;Jinglong Du;Maofeng Weng;Bao Ye
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.1
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    • pp.192-210
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    • 2024
  • Most frequency-domain remote sensing image watermarking algorithms embed watermarks at random locations, which have negative impact on the watermark invisibility. In this study, we propose an adaptive watermarking scheme for remote sensing images that considers the information complexity to select where to embed watermarks to improve watermark invisibility without affecting algorithm robustness. The scheme converts remote sensing images from RGB to YCbCr color space, performs two-level DWT on luminance Y, and selects the high frequency coefficient of the low frequency component (HHY2) as the watermark embedding domain. To achieve adaptive embedding, HHY2 is divided into several 8*8 blocks, the entropy of each sub-block is calculated, and the block with the maximum entropy is chosen as the watermark embedding location. During embedding phase, the watermark image is also decomposed by two-level DWT, and the resulting high frequency coefficient (HHW2) is then embedded into the block with maximum entropy using α- blending. The experimental results show that the watermarked remote sensing images have high fidelity, indicating good invisibility. Under varying degrees of geometric, cropping, filtering, and noise attacks, the proposed watermarking can always extract high identifiable watermark images. Moreover, it is extremely stable and impervious to attack intensity interference.

Matching Points Filtering Applied Panorama Image Processing Using SURF and RANSAC Algorithm (SURF와 RANSAC 알고리즘을 이용한 대응점 필터링 적용 파노라마 이미지 처리)

  • Kim, Jeongho;Kim, Daewon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.4
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    • pp.144-159
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    • 2014
  • Techniques for making a single panoramic image using multiple pictures are widely studied in many areas such as computer vision, computer graphics, etc. The panorama image can be applied to various fields like virtual reality, robot vision areas which require wide-angled shots as an useful way to overcome the limitations such as picture-angle, resolutions, and internal informations of an image taken from a single camera. It is so much meaningful in a point that a panoramic image usually provides better immersion feeling than a plain image. Although there are many ways to build a panoramic image, most of them are using the way of extracting feature points and matching points of each images for making a single panoramic image. In addition, those methods use the RANSAC(RANdom SAmple Consensus) algorithm with matching points and the Homography matrix to transform the image. The SURF(Speeded Up Robust Features) algorithm which is used in this paper to extract featuring points uses an image's black and white informations and local spatial informations. The SURF is widely being used since it is very much robust at detecting image's size, view-point changes, and additionally, faster than the SIFT(Scale Invariant Features Transform) algorithm. The SURF has a shortcoming of making an error which results in decreasing the RANSAC algorithm's performance speed when extracting image's feature points. As a result, this may increase the CPU usage occupation rate. The error of detecting matching points may role as a critical reason for disqualifying panoramic image's accuracy and lucidity. In this paper, in order to minimize errors of extracting matching points, we used $3{\times}3$ region's RGB pixel values around the matching points' coordinates to perform intermediate filtering process for removing wrong matching points. We have also presented analysis and evaluation results relating to enhanced working speed for producing a panorama image, CPU usage rate, extracted matching points' decreasing rate and accuracy.

Using a computer color image automatic detection algorithm for gastric cancer (컴퓨터 컬러 영상을 이용한 위암 자동검출 알고리즘)

  • Han, Hyun-Ji;Kim, Young-Mok;Lee, Ki-Young;Lee, Sang-Sik
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.4 no.4
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    • pp.250-257
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    • 2011
  • This experiment present the automatic detection algorithm of gastric cancer that take second place among all cancers. If an inflammation and a cancer are not examined carefully, early ones have difficulty in being diagnosed as illnesses than advanced ones. For diagnosis of gastric cancer, and progressing cancer in this study, present 4 algorithm. research team extracted an abnormal part in stomach through the endoscope image. At first, decide to use shading technique or not in each endoscope image for study. it make easy distinguish to whether tumor is existing or not by putting shading technique in or eliminate it by the color. Second. By passing image subjoin shading technique to erosion filter, eliminate noise and make give attention to diagnose. Third. Analyzing out a line and fillet graph from image adding surface shade and detect RED value according to degree of symptoms. Fourth. By suggesting this algorithm, that making each patient's endscope image into subdivision graph including RED graph value, afterward revers the color, revealing the position of tumor, this study desire to help to diagnosing gastric, other cancer and inflammation.

A Method for Effective Homography Estimation Applying a Depth Image-Based Filter (깊이 영상 기반 필터를 적용한 효과적인 호모그래피 추정 방법)

  • Joo, Yong-Joon;Hong, Myung-Duk;Yoon, Ui-Nyoung;Go, Seung-Hyun;Jo, Geun-Sik
    • KIPS Transactions on Software and Data Engineering
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    • v.8 no.2
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    • pp.61-66
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    • 2019
  • Augmented reality is a technology that makes a virtual object appear as if it exists in reality by composing a virtual object in real time with the image captured by the camera. In order to augment the virtual object on the object existing in reality, the homography of images utilized to estimate the position and orientation of the object. The homography can be estimated by applying the RANSAC algorithm to the feature points of the images. But the homography estimation method using the RANSAC algorithm has a problem that accurate homography can not be estimated when there are many feature points in the background. In this paper, we propose a method to filter feature points of a background when the object is near and the background is relatively far away. First, we classified the depth image into relatively near region and a distant region using the Otsu's method and improve homography estimation performance by filtering feature points on the relatively distant area. As a result of experiment, processing time is shortened 71.7% compared to a conventional homography estimation method, and the number of iterations of the RANSAC algorithm was reduced 69.4%, and Inlier rate was increased 16.9%.