• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1865-1872
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• 1997

This paper proposes not only the thresholding problem which has been one of the major problems in the pre-existing edge detection method but also the removal of blurring effect occurred at the edge regions due to the smoothing process. The structure of a given image is assigned as one of the three predefined image structure classes by evaluating its toll membership value to each reference structure class:The structure of an image belongs to the structure class which has the least cost value with the image. Upon the structure class assigned, noise removal and edge extraction precesses are performed, e.g., the smoothing algorithm is applied to the image if its structure belongs to the pure noise region class; edge extraction while removing the noise is performed simultaneously if the edge structure class. The proposed method shows that preventing the blurring effect can be usually seen in the edge images and extracting the edges with no using thresholding value by the experiments.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3718-3726
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• 1999

Color image is more effective than gray one in human visual perception. Therefore, color image processing becomes important area. Color images are often corrupted by noises due to the input sensor, channel transmission errors and so on. Some filtering techniques such as vector median, mean filter, and vector $\alpha-trimmed$ mean filter have been used for color noise removal. Among them, vector $\alpha-trimmed$ mean filter gave the best performance in the mixed color noise. But, there are edge shift and blurring effect because vector $\alpha-trimmed$ mean filter is uniformly processed across the image. So, we proposed a conditional fuzzy cluster filter to improve this problems. Simulation results showed that the proposed scheme improves the NCD measure and visual quality over the conventional vector $\alpha-trimmed$ mean filter in the mixed color noise.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.658-665
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• 2015

In the production of medical images, noise reduction and contrast enhancement are important methods to increase qualities of processing results. By using the edge-based denoising and adaptive nonlinear histogram stretching, a novel medical image enhancement algorithm is proposed. First, a medical image is decomposed by wavelet transform, and then all high frequency sub-images are decomposed by Haar transform. At the same time, edge detection with Sobel operator is performed. Second, noises in all high frequency sub-images are reduced by edge-based soft-threshold method. Third, high frequency coefficients are further enhanced by adaptive weight values in different sub-images. Finally, an adaptive nonlinear histogram stretching method is applied to increase the contrast of resultant image. Experimental results show that the proposed algorithm can enhance a low contrast medical image while preserving edges effectively without blurring the details.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.19-27
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• 2020

In this study, Developing high resolution camera and Social Network Service sharing image can be easily getting images, it cause about taking fingerprints to easy from images. So I present solution about prevent to taking fingerprints. this technology is develop python using to opencv, blur libraries. First of all 'Hand Key point Detection' algorithm is used to locate the hand in the image. Using this algorithm can be find finger joints that can be protected while minimizing damage in the original image by using the coordinates of separate blurring the area of fingerprints in the image. from now on the development of accurate finger tracking algorithms, fingerprints will be protected by using technology as an internal option for smartphone camera apps from high resolution images.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.891-894
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• 1998

This paper introduces an automatic face region extraction method. This method consists of two part: face recognition and extraction of facial organs which are eye, eyebrow, nose and mouth. In first stage, we use genetic algorithms(GAs) to get face region in complex background. In second stage, we use Geometrical Face Model to textract eye, eyebrow, nose and mouth. In both stage, stochastic component is used to deal with the problems caused by had lighting condition. According to this value, blurring number is determined. Average Computation time is less than 1 sec, and using this method we can extract facial feature efficiently from several images which has different lightning condition.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.563-566
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• 2003

Quality measures play an important role in the field of image processing. Such measures are commonly used to assess the performance of different algorithms that are designed to perform a specific image processing task. In this paper we propose two novel measures for image quality assessment based on the notion of correlation between fuzzy sets. Two different definitions fur the correlation between fuzzy sets have been used. In order to calculate the proposed quality measures two approaches were evaluated, one with direct application of the measures to the image′s pixels and the other using the fuzzy set corresponding to the normalized histogram of the image. A comparative study of the proposed measures is performed by investigating their behavior using images with different types of distortions, such as impulsive "salt at pepper" noise, additive white Gaussian noise, multiplicative speckle noise, blurring, gamma distortion, and JPEG compression.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1980-1987
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• 2000

In this paper, an efficient watermarking technique in wavelet transform domain is proposed. Watermarking is embedding a digital signal called as 'watermark' into images to claim the ownership. In the proposed method, the image is 1-level wavelet transformed, and then the watermark with a binary stamp is embedded into the baseband. The watermark is embedded by inverting the polarities of he selected coefficient paris. In the inverting process, we can increase image quality by finding means and differences of the selected neighboring coefficient paris, and then adding values, which are inversely proportional to the differences, to th means. The experimental results show that the proposed method has good quality and is robust to various attacks such as the JPEG lossy comparison, noise addition, clipping, blurring, etc.

• The Journal of Korea Robotics Society
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• v.5 no.4
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• pp.367-376
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• 2010

This Paper Proposes A Robust Image Stabilization System For A Mobile Robot Using An Extended Kalman Filter (Ekf). Though Image Information Is One Of The Most Efficient Data Used For Robot Navigation, It Is Subjected To Noise Which Is The Result Of Internal Vibration As Well As External Factors Such As Uneven Terrain, Stairs, Or Marshy Surfaces. The Camera Vibration Deteriorates The Image Resolution By Destroying The Image Sharpness, Which Seriously Prevents Mobile Robots From Recognizing Their Environment For Navigation. In This Paper, An Inclinometer Was Used To Measure The Vibration Angle Of The Camera System Mounted On The Robot To Obtain A Reliable Image By Compensating For The Angle Of The Camera Vibration. In Addition The Angle Prediction Obtained By Using The Ekf Enhances The Image Response Analysis For Real Time Performance. The Experimental Results Show The Effectiveness Of The Proposed System Used To Compensate For The Blurring Of The Images.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.827-830
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• 2008

We proposed a new Mercury-free flat fluorescent lamp (MFFL) for LCD backlight which has the scanning ability to reduce the blurring edges of moving images. We expanded the single cell MFFL with 2.2 inch diagonal size into the multi-cell MFFL for the 32-inch LCD-TV backlight application, and examined its response characteristics and proposed a driving scheme for scanning.

• Journal of information and communication convergence engineering
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• v.15 no.2
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• pp.131-136
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• 2017

Chest X-ray image cannot be focused in the same manner as optical lenses and the resultant image generally tends to be slightly blurred. Therefore, appropriate methods to improve the quality of chest X-ray image have been studied in this paper. As the frequency domain filters work well for slight blurring and moderate levels of additive noises, we propose an algorithm that is particularly suitable for enhancing chest image. First, the chest image using Gaussian high pass filter and the optimal high frequency emphasis filter shows improvements in the edges and contrast of the flat areas. Second, as compared to using histogram equalization where each pixel of chest image is characterized by a loss of detail and much noises, in using fuzzy logic, each pixel of chest image shows the detail preservation and little noise.