• 제목/요약/키워드: image assessment

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Accurate Camera Self-Calibration based on Image Quality Assessment

  • Fayyaz, Rabia;Rhee, Eun Joo
    • Journal of Information Technology Applications and Management
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    • 제25권2호
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    • pp.41-52
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    • 2018
  • This paper presents a method for accurate camera self-calibration based on SIFT Feature Detection and image quality assessment. We performed image quality assessment to select high quality images for the camera self-calibration process. We defined high quality images as those that contain little or no blur, and have maximum contrast among images captured within a short period. The image quality assessment includes blur detection and contrast assessment. Blur detection is based on the statistical analysis of energy and standard deviation of high frequency components of the images using Discrete Cosine Transform. Contrast assessment is based on contrast measurement and selection of the high contrast images among some images captured in a short period. Experimental results show little or no distortion in the perspective view of the images. Thus, the suggested method achieves camera self-calibration accuracy of approximately 93%.

Video Quality Assessment based on Deep Neural Network

  • Zhiming Shi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권8호
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    • pp.2053-2067
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    • 2023
  • This paper proposes two video quality assessment methods based on deep neural network. (i)The first method uses the IQF-CNN (convolution neural network based on image quality features) to build image quality assessment method. The LIVE image database is used to test this method, the experiment show that it is effective. Therefore, this method is extended to the video quality assessment. At first every image frame of video is predicted, next the relationship between different image frames are analyzed by the hysteresis function and different window function to improve the accuracy of video quality assessment. (ii)The second method proposes a video quality assessment method based on convolution neural network (CNN) and gated circular unit network (GRU). First, the spatial features of video frames are extracted using CNN network, next the temporal features of the video frame using GRU network. Finally the extracted temporal and spatial features are analyzed by full connection layer of CNN network to obtain the video quality assessment score. All the above proposed methods are verified on the video databases, and compared with other methods.

Subjective Imaging Effect Assessment for Intelligent Imaging Terminal Design: a Method for Engineering Site

  • Liu, Haoting;Lv, Ming;Yu, Weiqun;Guo, Zhenhui;Li, Xin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권3호
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    • pp.1043-1064
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    • 2020
  • A kind of Subjective Imaging Effect Assessment (SIEA) method and its applications on intelligent imaging terminal design in engineering site are presented. First, some visual assessment indices are used to characterize the imaging effect: the image brightness, the image brightness uniformity, the color image contrast, the image edge blur, the image color difference, the image saturation, the image noise, and the integrated imaging effect index. A linear weighted function is employed to carry out the SIEA computation and the Analytic Hierarchy Process (AHP) technique is used to estimate its weights. Second, a SIEA software is developed. It can play images after the settings of assessment index or assessment reaction time, etc. Third, two cases are used to illustrate the application effects of proposed method: the image enhancement system design for surveillance camera and the imaging environment perception system design for intelligent lighting terminal. A Prior Sequential Stimulus (PSS) experiment is proposed to improve the evaluation stability of SIEA method. Many experiment results have shown the proposed method can realize a stable system design or parameters setting for the intelligent imaging terminal in engineering site.

Development of the Korean Handwriting Assessment for Children Using Digital Image Processing

  • Lee, Cho Hee;Kim, Eun Bin;Lee, Onseok;Kim, Eun Young
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권8호
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    • pp.4241-4254
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    • 2019
  • The efficiency and accuracy of handwriting measurement could be improved by adopting digital image processing. This study developed a computer-based Korean Handwriting Assessment tool. Second graders participated in this study by performing writing tasks of consonants, vowels, words, and sentences. We extracted boundary parameters for each letter using digital image processing and calculated the variables of size, size coefficient of variation (CV), misalignment, inter-letter space, inter-word space, and ratio of inter-letter space to inter-word space. Children were also administered traditional handwriting and visuomotor tests. Digital variables from image processing were correlated with these previous tests. Using these correlations, we established a three-point scoring system that computed test scores for each variable. We analyzed inter-rater reliability between the computer rater and human rater and test-retest reliability between the first and second performances. The validity was examined by analyzing the relationship between the Korean Handwriting Assessment and previous handwriting and visuomotor tests. We suggested the Korean Handwriting Assessment to measure size, size consistency, misalignment, inter-letter space, inter-word space, and space ratio using digital image processing. This Korean Handwriting Assessment tool proved to have reliability and validity. It is expected to be useful for assessing children's handwriting.

Image Fidelity Assessment Using the Edge Histogram Descriptor of MPEG-7

  • Won, Chee-Sun
    • ETRI Journal
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    • 제29권5호
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    • pp.703-705
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    • 2007
  • An image fidelity assessment using the edge histogram descriptor (EHD) of MPEG-7 is presented. Neither additional data nor fragile watermarking is needed, and there is no need to access the original image as a reference. Only the EHDs of the original image and the received image are required. The peak signal-to-noise ratio (PSNR) obtained by comparing the EHD extracted from the received image and that of the original image is used to assess the noise level of the received image. Experimental results show that the PSNRs calculated from the conventional pixel-to-pixel gray level and from the proposed bin-to-bin EHD maintain a proportional relationship. This implies that the EHD can be used instead of image data for the image fidelity assessments.

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스테레오스코픽 3D영상 화질 평가 방법 (A Method of Stereoscopic 3D Image Quality Assessment)

  • 박영수;허남호;표경수;송정근
    • 방송공학회논문지
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    • 제16권2호
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    • pp.319-330
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    • 2011
  • 스테레오스코픽 3D 영상의 객관적인 화질 평가를 위해서 지금까지는 왼쪽과 오른쪽 영상에 대해 각각 2D 영상의 화질을 측정, 평가하는 방법을 사용하였다. 하지만 이 방법은 각각의 영상에 대해서 별도로 화질을 평가해야 하는 불편함이 따랐다. 그래서 본 논문에서는 왼쪽과 오른쪽 영상을 중첩하여 만든 하나의 영상을 통하여 스테레오스코픽 3D 영상의 화질을 평가하는 방법을 제안하여, 보다 간편하고 빠르게 스테레오스코픽 3D 영상의 화질을 평가할 수 있도록 하였다.

그래디언트 히스토그램 기반의 효율적인 영상 품질 평가 (Histogram of Gradient based Efficient Image Quality Assessment)

  • 노세용;안상우;정정화
    • 전기전자학회논문지
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    • 제16권3호
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    • pp.182-188
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    • 2012
  • 본 논문에서는 그래디언트 히스토그램을 기반으로 하는 영상 품질 평가 알고리즘을 제안하였다. 이는 목표 영상의 그래디언트 영상을 히스토그램으로 나타낼 경우 영상의 특성을 잘 나타낸다는 장점을 이용하였다. 제안한 방법에서 영상의 품질은 목표 영상에서 얻어진 그래디언트 히스토그램의 기울기에 의해 평가되고, 그래디언트 히스토그램을 대표하는 선의 기울기는 RANSAC (Random Sample Consensus)에 의해 측정된다. LIVE 영상 품질 평가 데이터베이스를 사용한 실험 결과를 통하여 제안한 알고리즘이 현존하는 다른 알고리즘에 비해 실제 사람의 영상에 대한 평가와 유사하다는 것을 확인할 수 있다.

Analysis of Image Quality Based on Perceptual Vision

  • Xue, Liqin;Hua, Yuning;Qi, Yaping
    • 한국정보디스플레이학회:학술대회논문집
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    • 한국정보디스플레이학회 2007년도 7th International Meeting on Information Display 제7권2호
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    • pp.1494-1496
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    • 2007
  • This paper deals with image quality analysis considering the impact of psychological factors involved in assessment. The attributes of image quality requirement were partitioned according to the visual perception characteristics and the preference of image quality were obtained by the factor analysis method. The features of image quality which support the subjective preference were identified, The adequacy of image is evidenced to be the top requirement issues to the display image quality improvement.

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Region of Interest Heterogeneity Assessment for Image using Texture Analysis

  • Park, Yong Sung;Kang, Joo Hyun;Lim, Sang Moo;Woo, Sang-Keun
    • 한국컴퓨터정보학회논문지
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    • 제21권11호
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    • pp.17-21
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    • 2016
  • Heterogeneity assessment of tumor in oncology is important for diagnosis of cancer and therapy. The aim of this study was performed assess heterogeneity tumor region in PET image using texture analysis. For assessment of heterogeneity tumor in PET image, we inserted sphere phantom in torso phantom. Cu-64 labeled radioisotope was administrated by 156.84 MBq in torso phantom. PET/CT image was acquired by PET/CT scanner (Discovery 710, GE Healthcare, Milwaukee, WI). The texture analysis of PET images was calculated using occurrence probability of gray level co-occurrence matrix. Energy and entropy is one of results of texture analysis. We performed the texture analysis in tumor, liver, and background. Assessment textural features of region-of-interest (ROI) in torso phantom used in-house software. We calculated the textural features of torso phantom in PET image using texture analysis. Calculated entropy in tumor, liver, and background were 5.322, 7.639, and 7.818. The further study will perform assessment of heterogeneity using clinical tumor PET image.

Blind Image Quality Assessment on Gaussian Blur Images

  • Wang, Liping;Wang, Chengyou;Zhou, Xiao
    • Journal of Information Processing Systems
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    • 제13권3호
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    • pp.448-463
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    • 2017
  • Multimedia is a ubiquitous and indispensable part of our daily life and learning such as audio, image, and video. Objective and subjective quality evaluations play an important role in various multimedia applications. Blind image quality assessment (BIQA) is used to indicate the perceptual quality of a distorted image, while its reference image is not considered and used. Blur is one of the common image distortions. In this paper, we propose a novel BIQA index for Gaussian blur distortion based on the fact that images with different blur degree will have different changes through the same blur. We describe this discrimination from three aspects: color, edge, and structure. For color, we adopt color histogram; for edge, we use edge intensity map, and saliency map is used as the weighting function to be consistent with human visual system (HVS); for structure, we use structure tensor and structural similarity (SSIM) index. Numerous experiments based on four benchmark databases show that our proposed index is highly consistent with the subjective quality assessment.