• Proceedings of the KSME Conference
• /
• 2003.04a
• /
• pp.845-850
• /
• 2003

The scattered light pattern from a machined surface generally contains much information concerning the surface roughness. The light pattern can be acquired by optical system and analyzed by statistical method. This kind of surface roughness measurement system can be easily adopted on the machine measurement. But the fully assembled system is too complex to implement on small systems using micro-controller. This study proposes the idea of reducing the number of optical components by removing screen and examines image processing of a light pattern to minimize the negative result of incomplete optical system. And the Gaussian blur filtering is concluded to be the best method of proposed measurement system. Furthermore light intensity variation of image pattern can be treated as a signal, therefore FIR filtering gives the similar result of Gaussian blur effect.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2002.11a
• /
• pp.213-216
• /
• 2002

The system realization for printimage enhancement of electrothermal printer using thermal historic management is presented. The thermal historic control technique reduces the blur that the high density thermal print head(TPH) and high speed printing in the 300dpi high is increased edge blur of printed image. The experiment result is that the system enhance the quality of print image.

• Journal of IKEEE
• /
• v.22 no.4
• /
• pp.1242-1245
• /
• 2018

In this paper, we have implemented a network that overcomes the over-blurring phenomenon that occurs when removing Gaussian noise. In the conventional filtering method, blurring of the original image is performed to remove noise, thereby eliminating high frequency components such as edges and corners. We propose a network that reducing over blurring while maintaining denoising performance by adding denoised high frequency components to denoisers based on CNN.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2009.10a
• /
• pp.1164-1167
• /
• 2009

Motion-image-quality of LCD-TVs is discussed by dynamic spatial frequency response. Smaller temporal aperture or higher frame rate can improve dynamic response, but an increase of motion velocity easily cancels the improvement. A guideline for deciding the desirable temporal aperture and frame rate of LCD-TVs is described, under the condition that camera and display have the same parameters. Two candidates of the desirable parameter sets will be (240 or 300 Hz, 50 to 100% aperture) and (120Hz, 25 to 50% aperture), from the viewpoint of "limit of acceptance" on motion-imagequality-deterioration for critical picture materials.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2785-2788
• /
• 2001

In this paper, we present a new interpolation scheme for image enhancement using fuzzy inference. In general, interpolation techniques are based on linear operators which are essentially lowpass filters, hence, they tend to blur fine details in the original image. In our approach, the operator itself balances the strength of its sharpening and noise suppressing components according to the properties of the input image data.

• Journal of Korea Multimedia Society
• /
• v.14 no.11
• /
• pp.1392-1400
• /
• 2011

In most digital imaging applications, high-resolution images or videos are usually desired for later image processing and analysis. The image signal obtained from general imaging system occurs image degradation during the process of image acquirement caused by the optics, physical constraints and the atmosphere effects. Super-resolution reconstruction, one of the solution to address this problem, is image reconstruction technique that produces a high-resolution image from several low-resolution frames in video sequences. In this paper, we propose an improved super-resolution method using Projection onto Convex Sets (POCS) method based on Shift & Add (S&A). The image using conventional algorithms is sensitive to noise. To solve this problem, we propose a fusion algorithm of S&A and POCS. Also we solve the problem using BLPF (Butterworth Low-pass Filter) in frequency domain as optical blur. Our method is robust to noise and has sharpness enhancement ability. Experimental results show that the proposed super-resolution method has better resolution enhancement performance than other super-resolution methods.

• Journal of The Korean Association of Information Education
• /
• v.15 no.3
• /
• pp.517-524
• /
• 2011

This paper presents a fast blind deconvolution method that produces a deblurring result from a single image in only a few seconds. The high speed of our method is enabled by considering the Discrete Fourier Transform (DFT), and its relation to filtering and convolution, and fast computation of Moore-Penrose inverse matrix. How can we predict the behavior of an arbitrary filter, or even more to the point design a filter to achieve certain specifications. The idea is to study the frequency response of the filter. This concept leads to an useful convolution formula. A Matlab implementation of our method usually takes less than one minute to deblur an image of moderate size, while the deblurring quality is comparable.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.3
• /
• pp.740-753
• /
• 2023

Text recognition in natural scene images is a challenging problem in computer vision. The accurate identification of ship number characters can effectively improve the level of ship traffic management. However, due to the blurring caused by motion and text occlusion, the accuracy of ship number recognition is difficult to meet the actual requirements. To solve these problems, this paper proposes a dual-branch network based on the CRNN identification network. The network couples image restoration and character recognition. The CycleGAN module is used for blur restoration branch, and the Pix2pix module is used for character occlusion branch. The two are coupled to reduce the impact of image blur and occlusion. Input the recovered image into the text recognition branch to improve the recognition accuracy. After a lot of experiments, the model is robust and easy to train. Experiments on CTW datasets and real ship maps illustrate that our method can get more accurate results.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2009.10a
• /
• pp.1363-1366
• /
• 2009

A new recognition method is used to find the three-dimensional target object on integral imaging. For finding the location of a target image, amount of reconstructed reference image is needed. This method is giving accurate information of target image by correlated among reconstructed target images and reference images.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.23 no.5
• /
• pp.726-731
• /
• 1986

An effective filtering algorithm which can reduce noise and preserve edges for the restoration of an image degraded by additive white Gaussian noise is presented. The algorithm proposed in this paper is an extension of Lee's algorithm modified to use local gradient information as well as local statistics. It does not require image modeling, and removes noise along the orientaiton of edges so that it does not blur the edge.