• Title/Summary/Keyword: 이미지 히스토그램

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Study on an Extraction Method for a Fuel Rod Image and a Visualization of the Color Information in a Sectional Image of a Spent Fuel Assembly (사용후핵연료집합체 영상에서 핵연료봉 영상 추출방법과 색상정보의 가시화에 관한 연구)

  • Jang, Ji-Woon;Shin, Hee-Sung;Youn, Cheung;Kim, Ho-Dong
    • Journal of the Korean Society for Nondestructive Testing
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    • v.27 no.5
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    • pp.432-441
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    • 2007
  • Image processing methods for an extraction of a nuclear fuel rod image and visualization methods of the RGB color data were studied with a sectional image of spent fuel assembly. The fuel rod images could be extracted by using a histogram analysis, an edge detection and RGB rotor data. In these results, a size of the spent fuel assembly could be measured by using a histogram analysis method and a shape of the spent fuel rod could be observed by using an edge detection method. Finally, a various analyses were established for status of the spent fuel assembly by realized various 3D images for the color data in an image of a spent fuel assembly.

An Efficient Shaking Correction Techniques for Image Stabilization of Moving Vehicles (이동차량 영상 안정화를 위한 효율적인 흔들림 보정 기법)

  • Hong, Sung-Il;Lin, Chi-Ho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.14 no.3
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    • pp.155-162
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    • 2014
  • In this paper, we propose an efficient shaking correction techniques for a moving vehicle image stabilization. The proposed shaking correction techniques was calculated cumulative histogram for the conversion and the separating information via color separation of video image frame of the input received. And it were to matching the histogram for match the color information as compensation result of the shaking vehicle video imaging. In this paper, the proposed the shaking correction techniques was obtained to the restoration result when compared to the existing shaking correction techniques that the smallest noise and better the naturalness of image through stabilization of luminance level and color level. Also, the imaging stabilization method was demonstrated the efficiency compared to other methods through to the real-time processing without the use of the memory.

Proposal of a method of using HSV histogram data learning to provide additional information in object recognition (객체 인식의 추가정보제공을 위한 HSV 히스토그램 데이터 학습 활용 방법 제안)

  • Choi, Donggyu;Wang, Tae-su;Jang, Jongwook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.6-8
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    • 2022
  • Many systems that use images through object recognition using deep learning have provided various solutions beyond the existing methods. Many studies have proven its usability, and the actual control system shows the possibility of using it to make people's work more convenient. Many studies have proven its usability, and actual control systems make human tasks more convenient and show possible. However, with hardware-intensive performance, the development of models is facing some limitations, and the ease with the use and additional utilization of many unupdated models is falling. In this paper, we propose how to increase utilization and accuracy by providing additional information on the emotional regions of colors and objects by utilizing learning and weights from HSV color histograms of local image data recognized after conventional stereotyped object recognition results.

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A Basic Study on the System of Converting Color Image into Sound (컬러이미지-소리 변환 시스템에 관한 기초연구)

  • Kim, Sung-Ill;Jung, Jin-Seung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.2
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    • pp.251-256
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    • 2010
  • This paper aims for developing the intelligent robot emulating human synesthetic skills which associate a color image with sound, so that we are able to build an application system based on the principle of mutual conversion between color image and sound. As the first step, in this study, we have tried to realize a basic system using the color image to sound conversion. This study describes a new conversion method to convert color image into sound, based on the likelihood in the physical frequency information between light and sound. In addition, we present the method of converting color image into sound using color model conversion as well as histograms in the converted color model. In the basis of the method proposed in this study, we built a basic system using Microsoft Visual C++(ver. 6.0). The simulation results revealed that the hue, saturation and intensity elements of a input color image were converted into F0, harmonic and octave elements of a sound, respectively. The converted sound elements were synthesized to generate a sound source with WAV file format using Csound toolkit.

Characteristics of Asphalt Pavement Images and Enhanced Algorithm for Noise Reduction (이미지프로세싱기법을 이용한 포장이미지의 특성과 노이즈제거를 위한 알고리즘 선정)

  • Kim, Jung-Yong;Cho, Yoon-Ho
    • International Journal of Highway Engineering
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    • v.3 no.4 s.10
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    • pp.137-146
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    • 2001
  • Pavement distresses are one of the most important data for pavement management systems. Inspection machines and its related programs have been used for operating tools in PMS developed in advanced countries. In Korea imported machines and programs for the length price ale utilized to get information of pavement condition from the field This study is launched for developing the program which can detect cracks on asphalt pavement due to many drawbacks in current PMS operation such as improper maintenance work and long resting period when it was broken. The focus of this study is to define principles to analyze pavement surface with digital image processing techniques, to test property of pavement images and to suggest an algorithm that reduces noises at test. To test images, the camera attached on the Automatic Road Analyser(ARAN) was used. Through the FFT images, histogram and statistical values of pavement images, it was found that the images had many noises with high-frequency components against general images, and it was difficult to subdivide pavement images into background or crack. Through several testing with various filters for noise reduction a 3X3 median filter was suggested to reduce noises effectively.

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Reversible Data Embedding Algorithm based on Pixel Value Prediction Scheme using Local Similarity in Image (지역적 유사성을 이용한 픽셀 값 예측 기법에 기초한 가역 데이터 은닉 알고리즘)

  • Jung, Soo-Mok
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.10 no.6
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    • pp.617-625
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    • 2017
  • In this paper, an effective reversible data embedding algorithm was proposed to embed secrete data into image. In the proposed algorithm, prediction image is generated by accurately predicting pixel values using local similarity existing in image, difference sequence is generated using the generated prediction image and original cover image, and then histogram shift technique is applied to create a stego-image with secrete data hidden. Applying the proposed algorithm, secrete data can be extracted from the stego-image and the original cover image can be restored without loss. Experimental results show that it is possible to embed more secrete data into cover image than APD algorithm by applying the proposed algorithm.

Musical Score Recognition Using Hierarchical ART2 Algorithm (Hierarchical ART2 알고리즘을 이용한 악보 인식)

  • Kim, Kwang-Baek;Woo, Young-Woon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.10
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    • pp.1997-2003
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    • 2009
  • Methods for effective musical score recognition and efficient editing of musical scores are demanded because functions of computers for researches on musical activities become more and more important parts in recent days. In the conventional methods for handling musical scores manually, there are weak points such as incorrect score symbols in input process and requirement of much time to adjust the incorrect symbols. And also there is another weak point that the scores edited by each application program can be remodified by a specific application program only. In this paper, we proposed a method for automatic musical score recognition of printed musical scores in order to make up for the weak points. In the proposed method, staffs in a scanned score image are eliminated by horizontal histogram, noises are removed by 4 directional edge tracking algorithm, and then musical score symbols are extracted by using Grassfire algorithm. The extracted symbols are recognized by hierarchical ART2 algorithm. In order to evaluate the performance of the proposed method, we used 100 musical scores for experiment. In the experiment, we verified that the proposed method using hierarchical ART2 algorithm is efficient.

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%.

Design of Optimized RBFNNs based on Night Vision Face Recognition Simulator Using the 2D2 PCA Algorithm ((2D)2 PCA알고리즘을 이용한 최적 RBFNNs 기반 나이트비전 얼굴인식 시뮬레이터 설계)

  • Jang, Byoung-Hee;Kim, Hyun-Ki;Oh, Sung-Kwun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.1
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    • pp.1-6
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    • 2014
  • In this study, we propose optimized RBFNNs based on night vision face recognition simulator with the aid of $(2D)^2$ PCA algorithm. It is difficult to obtain the night image for performing face recognition due to low brightness in case of image acquired through CCD camera at night. For this reason, a night vision camera is used to get images at night. Ada-Boost algorithm is also used for the detection of face images on both face and non-face image area. And the minimization of distortion phenomenon of the images is carried out by using the histogram equalization. These high-dimensional images are reduced to low-dimensional images by using $(2D)^2$ PCA algorithm. Face recognition is performed through polynomial-based RBFNNs classifier, and the essential design parameters of the classifiers are optimized by means of Differential Evolution(DE). The performance evaluation of the optimized RBFNNs based on $(2D)^2$ PCA is carried out with the aid of night vision face recognition system and IC&CI Lab data.

An Advanced Watermarking Algorithm with Reversibility (개선된 가역 워터마킹 알고리즘)

  • Jung, Soo-Mok
    • Journal of the Korea Convergence Society
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    • v.9 no.2
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    • pp.151-156
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    • 2018
  • In this paper, an efficient reversible watermarking algorithm is proposed. By using the proposed algorithm, it is possible to increase the amount of copyright-related information to be embedded in cover image. Depending on the spatial locality and surface characteristics, it is possible to precisely predict the pixel value using neighboring pixels. If the predicted pixel value almost the same as the pixel value of the cover image, the differential value between the predicted pixel value and the pixel value of cover image is very small. So, the frequency is increased greatly at the peak point of histogram of difference sequence. Thus, it is possible to increase greatly the amount of secret data to be embedded in cover image. The experimental results show that the proposed watermarking algorithm is superior to the previous algorithms.