• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.2927-2936
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• 2013

In this paper, we propose a noise reduction and hole removal algorithm in order to improve the quality of depth images when they are used for creating 3D contents. In the proposed algorithm, the depth image and the corresponding color image are both used. First, an intensity image is generated by converting the RGB color space into the HSI color space. By estimating the difference of distance and depth between reference and neighbor pixels from the depth image and difference of intensity values from the color image, they are used to remove noise in the proposed algorithm. Then, the proposed hole filling method fills the detected holes with the difference of euclidean distance and intensity values between reference and neighbor pixels from the color image. Finally, we apply a parallel structure of GPGPU to the proposed algorithm to speed-up its processing time for real-time applications. The experimental results show that the proposed algorithm performs better than other conventional algorithms. Especially, the proposed algorithm is more effective in reducing edge blurring effect and removing noise and holes.

• Journal of radiological science and technology
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• v.47 no.1
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• pp.21-28
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• 2024

This study was purpose to quantitative evaluation of comparison of the image intensity uniformity and noise power spectrum (NPS) by using American college of radiology (ACR) phantom for magnetic resonance imaging (MRI). The MRI was used achiva 3.0T MRI and discovery MR 750, 3.0T, the head and neck matrix shim SENSE head coil were 32 channels receive MR coil. The MRI was used parameters of image sequence for ACR standard and general hospital. NPS value of the ACR standard T2 vertical image in GE equipment was 7.65E-06 when the frequency was 1.0 mm^-1. And the NPS value of the ACR hospital T1 region of interest (ROI) 9 over all vertical image in Philips equipment was 9E-08 when the frequency was 1.0 mm^-1 and the NPS value of the hospital T2 ROI 9 over all vertical image in Philips equipment was 1.06E-07 when the frequency was 1.0 mm^-1. NPS was used efficiently by using a general hospital vertical sequence more than the standard vertical sequence method by using the ACR phantom. Furthermore NPS was the quantitative quality assurance (QA) assessment method for noise and image intensity uniformity characteristics was applied mutatis mutandis, and the results values of the physical imaging NPS of the 3.0T MRI and ACR phantom were presented.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.111-118
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• 1996

A content-based image retrieval system is designed and implemetned using the color featurees which are histogram intersection and color pairs. The preprocessor for the image retrieval manage linearly the existing HSI(hue, saturation, saturation, intensity). Hue and intensity histogram thresholding for each color attribute is performed to split the chromatic and achromatic regions respectively. Grouping te indexes produced by the histogram intersection is used to save the retrieval times. Each image is divided into the cells of 32$\times$32 pixels, and color pairs are used to represent the query during retrievals. The recall/precision of histogram intersection is 0.621/0.663 and recall/precision of color pairs is 0.438/0.536. And recall/precision of proposed method is 0.765/0.775/. It is shown that the proposed method using histogram intersection and color pairs improves the retrieval rates.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.181-185
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• 1996

Color image is largely corrupted by various ambient illumination. However, human perceives always white color as white under any illumination because of a characteristic of human vision, called color constancy. In the conventional algorithm which applied the constancy effect, after the RGB color space is transformed to the IHS(Intensity, Hue, and Saturation) color space, then the hue is preserved and the intensity or the saturation is properly enhanced. Then the enhanced IHS color is reversely transformed to the RGB color space. In this process, the color distortion is included due to the color gamut error. But in the proposed algorithm, there is not transformation. In that, the RGB color is considered as 3 dimensional color vector and we assume that white color is the natural daylight. As the color vector of the illumination can be calculated as the average vector of R, G, and B image, we can achieve the constancy effect by simply rotating the illumination vector to the white color vector. The simulation results show the efficiency of the vector rotating process for color image enhancement.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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• pp.1543-1544
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• 2007

Carbon nanotubes (CNTs) are coated on green $ZnGa_2O_4:Mn^{2+}$ phosphor for filed emission display. The cathodoluminescent intensity of CNTs-phosphor is improved compared with uncoated phosphors. Also the effects of phosphors-coated CNTs on electrical and degradation characteristics are investigated to reveal the reason of the enhanced emission intensity.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.729-734
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• 2005

One of the important research issues in mobile robot is how to detect the 3D environment fast and accurately, and recognize it. Sensing methods of utilizing laser structured light and/or stereo vision are representatively used among a number of methodologies developed to date. However, the methods are still in need of achieving high accuracy and reliability to be used for real world environments. In this paper to implement a new robotic environmental sensing algorithm is presented by combining the information between intensity image and that of laser structured light image. To see how effectively the algorithm applied to real environments, we developed a sensor system that can be mounted on a mobile robot and tested performance for a series of environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.7
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• pp.1464-1468
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• 2004

The color conversion and color enhancement on gray image is presented in this paper. The pseudocoloring for RCB color components extraction from gray image is used the 2D U(Fast Wavelet Transform) for fille. bank and re-array. The each post processing is used the median filtering for noise reduction and the discrete color histogram equalization for CIT(Color Intensity Transformation). The experiment result has enhanced pseudocoloring image as PSNR 30dB over compared the processing of normal wavelet transform.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.2
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• pp.63-69
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• 2012

Noise is regarded as an unwanted component of the image because it significantly reduces image quality. And image is often corrupted by mixed noise. In this paper an efficient modified weighted filter algorithm which combines spatial weight and intensity weight is proposed for removing mixed noise. In the proposed method, the filtering mask is separated into the four sub-windows and the parameters of the weights are confirmed by calculating local standard deviation and the mean of four sub-windows' standard deviations. Considering the spatial information and intensity information, the proposed method has good performance on not only noise elimination but also preservation of details. Simulation results demonstrate that the proposed method performs better than conventional algorithms.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.35-42
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• 2014

It is possible to improve the obstacle avoidance capability by training and recognizing the obstacles which is in certain indoor environment. We propose the technique that use underlying intensity value along with intensity map from RGB-D image which is derived from stereo vision Kinect sensor and recognize an obstacle within constant distance. We test and experiment the accuracy and execution time of the pattern recognition algorithms like PCA, ICA, LDA, SVM to show the recognition possibility of it. From the comparison experiment between RGB-D data and intensity data, RGB-D data got 4.2% better accuracy rate than intensity data but intensity data got 29% and 31% faster than RGB-D in terms of training time and intensity data got 70% and 33% faster than RGB-D in terms of testing time for LDA and SVM, respectively. So, LDA, SVM have good accuracy and better training/testing time to use for obstacle avoidance based on intensity dataset of mobile robot.

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.126-130
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• 2007

This paper proposes a method that automatically extracts characteristics of cracks such as length, thickness and direction, etc., from a concrete surface image with image processing techniques. This paper, first, uses the closing morphologic operation to adjust the effect of light extending over the whole concrete surface image. After applying the high-pass filtering operation to sharpen boundaries of cracks, we classify intensity values of the image into 8 groups and remove intensity values belong to the highest frequency group among them for the removal of background. Then, we binarize the preprocessed image. The auxiliary lines used to measure cracks of concrete surface are removed from the binarized image with position information extracted by the histogram operation. Then, cracks broken by the removal of background are extended to reconstruct an original crack with the $5{\times}5$ masking operation. We remove unnecessary information by applying three types of noise removal operations successively and extracts areas of cracks from the binarized image. At last, the opening morphologic operation is applied to compensate extracted cracks and characteristics of cracks are measured on the compensated ones. Experiments using real images of concrete surface showed that the proposed method extracts cracks well and precisely measures characteristics of cracks.