• Current Optics and Photonics
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• v.8 no.2
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• pp.127-137
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• 2024

The distribution of tags is an important factor that affects the performance of radio-frequency identification (RFID). To study RFID performance, it is necessary to obtain RFID tags' coordinates. However, the positioning method of RFID technology has large errors, and is easily affected by the environment. Therefore, a new method using optical measurement is proposed to achieve RFID performance analysis. First, due to the possibility of blurring during image acquisition, the paper derives a new image prior to removing blurring. A nonlocal means-based method for image deconvolution is proposed. Experimental results show that the PSNR and SSIM indicators of our algorithm are better than those of a learning deep convolutional neural network and fast total variation. Second, an RFID dynamic testing system based on photoelectric sensing technology is designed. The reading distance of RFID and the three-dimensional coordinates of the tags are obtained. Finally, deep learning is used to model the RFID reading distance and tag distribution. The error is 3.02%, which is better than other algorithms such as a particle-swarm optimization back-propagation neural network, an extreme learning machine, and a deep neural network. The paper proposes the use of optical methods to measure and collect RFID data, and to analyze and predict RFID performance. This provides a new method for testing RFID performance.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.551-566
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• 2016

In the satellite remote sensing, the operational environment of the satellite sensor causes image degradation during the image acquisition. The degradation results in noise and blurring which badly affect identification and extraction of useful information in image data. Especially, the degradation gives bad influence in the analysis of images collected over the scene with complicate surface structure such as urban area. This study proposes a multi-stage image restoration to improve the accuracy of detailed analysis for the images collected over the complicate scene. The proposed method assumes a Gaussian additive noise, Markov random field of spatial continuity, and blurring proportional to the distance between the pixels. Point-Jacobian Iteration Maximum A Posteriori (PJI-MAP) estimation is employed to restore a degraded image. The multi-stage process includes the image segmentation performing region merging after pixel-linking. A dissimilarity coefficient combining homogeneity and contrast is proposed for image segmentation. In this study, the proposed method was quantitatively evaluated using simulation data and was also applied to the two panchromatic images of super-high resolution: Dubaisat-2 data of 1m resolution from LA, USA and KOMPSAT3 data of 0.7 m resolution from Daejeon in the Korean peninsula. The experimental results imply that it can improve analytical accuracy in the application of remote sensing high resolution panchromatic imagery.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.81-84
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• 2000

Cellular automata are discrete dynamical systems whose behaviour is completely specified in terms of a local relation. If cellular automata convergence to fixed points, then it can be used to image processing. From the generalized Potts automata point of view, we propose in this paper a cellular automata technique for reducing image noise. To minimize blurring effect, an algorithm based on neighborhood median computation is Preferred. Experimental results are reported.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.233-236
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• 1996

A new method of blocking effects reduction is proposed in this paper for use in low bitrate image coding. We use 28 DCT kernel functions of which boundary values are linearly independent, and Gram-Schmidt process is applied to the boundary values in order to obtain 28 boundary-orthonormal basis images. Then we use these basis images to obtain the correction terms for blocking artifacts reduction. A threshold of block discontinuity is introduced for improvement of visual quality by reducing image blurring. We also investigate the number of basis images needed for efficient blocking artifacts reduction when the compression ratio changes.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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• pp.1143-1146
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• 2007

We carried out the human visual evaluation on PDPs and LCDs to clarify the viewer preference and the related physical and physiological factors. In the subjective evaluation, the impression test using the semantic differential method was carried out. In the objective evaluation, the eye motion tracking system was used. Our study showed that considering the real usage, the optimum display for viewers was that which showed more soft and smooth image without blurring.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.525-533
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• 2003

In this paper we introduce some existing preprocessing algorithm for character recognition and consider feature extraction method for the recognition of low resolution document. Image recognition of low resolution document including fax images can be frequently misclassified due to the blurring effect, slope effect, noise and so on. In order to overcome these difficulties in the character recognition we considered a mesh feature extraction and contour direction code feature. System for automatic character recognition were suggested.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1991.10a
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• pp.77-80
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• 1991

This paper proposes a new feature extraction method which is effectively used in character recognition, and validate the effectiveness through various computational methods for similiarity degree. To get feature vectors used in this method, Hough transform is applied to character image, which is used for edge extraction in image processing. By that transformation technique, strokes could be extracted and feature vectors constructed suitably. The characteristic of this method is solving the difficulties in stroke extraction through transform space analysis, which is induced by noise and blurring, and representing high recognition rate 99.3% within 10 candidates in relative low dimension.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.11a
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• pp.87-90
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• 1997

본 논문에서는 영상의 잡음(noise) 제거를 위한 새로운 diffusion모델을 제안한다. MOD모델 (mean curvature diffusion model)은 영상의 잡음 제거 때 유발되는 경계선의 blurring을 지양할 수 있는 장점이 있는 반면에 수렴상태(convergence state)를 갖지 못한 단점을 안고 있다. 본 논문에서는 MCD 모델에 min/max switch를 결합시킴으로써 MCD모델이 갖고 있던 문제점을 개선하였다. 제안하는 diffusion 모델은 scheme의 반복적인 적용에 대해서 실질적으로 그 결과가 더 이상 변동하지 않는 수렴상태(convergence state)를 가진 매우 안정적인 시스템이다.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.373-376
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• 2002

This paper represents a survey of a variety thresholding techniques including both global and local thresholding. Several thresholding methods are examined in detail to evaluate their performance based on a given set of test images. We also attempt to evaluate the performance of several thresholding methods for construction field documents image recognition system using a broken line structures, broken symbols and text, blurring of lines, symbols and text, noise in homogeneous areas measure as a criterion functions.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.355-358
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• 2012

Although quality metrics for 2D video quality assessment have been proposed, the quality models on stereoscopic video have not been widely studied. In this paper, a new objective video quality metric for s tereoscopic video is proposed. The proposed algorithm consider three factors to evaluate stereoscopic video quality: blocking artifact, blurring artifact, and the difference between left and right view of stereoscopic vide o. The results show that the proposed algorithm has a higher correlation with DMOS than the others.