• Journal of Information Technology Applications and Management
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• v.25 no.2
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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%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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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.

• ETRI Journal
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• v.29 no.5
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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.

• Journal of Broadcast Engineering
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• v.16 no.2
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• pp.319-330
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• 2011

For objective assessment of stereoscopic 3D image quality, we measure quality of left and right image with 2D image quality measurement method. However, this method is inconvenient because that we have to measure quality of left and right image individually. Therefore we propose a method of stereoscopic 3D image quality assessment using one overlaid image with left and right image. Using this method, One can measure quality of stereoscopic 3D image more easily and quickly.

• Journal of IKEEE
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• v.16 no.3
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• pp.182-188
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• 2012

Here we propose an image quality assessment (IQA) based on histogram of oriented gradients (HOG). This method makes use of the characteristic that the histogram of gradient image describes the state of input image. In the proposed method, the image quality is derived by the slope of the HOG obtained from the target image. The line representing the HOG is measured by a random sample consensus (RANSAC) on the HOG. Simulation results based on the LIVE image quality assessment database suggest that the proposed method aligns better with how the human visual system perceives image quality than several state-of-the-art IQAs.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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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.

• Journal of the Korea Society of Computer and Information
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• v.21 no.11
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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.

• Journal of Information Processing Systems
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• v.13 no.3
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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.