• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2002.12a
• /
• pp.317-320
• /
• 2002

In this paper, an automatic histogram specification method is proposed for image enhancement, Fuzzy membership value is adopted for the representation of image histogram. The desired PDF is automatically constructed by the fuzzy membership value. Fuzzy membership value is extracted from dark membership, bright membership function and original histogram. The effectual results are demonstrated by desired PDF which meet the image enhancement requirements. The performance and effectiveness are shown by the analysis and the resultant image in comparison with histogram equalization method.

• Fibers and Polymers
• /
• v.6 no.2
• /
• pp.156-161
• /
• 2005

The gray line-profile method is introduced to find fabric density. Some patterned fabrics like stripe design as well as solid fabrics of basic weave structures are used to verify the efficiency and accuracy of the method. The approach is compared with Fourier transform method. Although the gray line-profile method is concise, it shows good results in both solid and patterned fabrics. In addition, it does not require a pre-processing or filtering technique in space or frequency domain to enhance the image suitable for the analysis. However, the approach is slightly influenced by the filter size for finding the local minimums of profile graph.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.11 no.5
• /
• pp.60-69
• /
• 2003

The simplified two-color method is proposed which can estimate the temperature distribution and the soot density of the whole flame with the image analysis of the high-speed photographs. The factors influenced on its processing were examined, for example, the selection of the wave length, the kind of films, the preparation of the calibration curve between the radiance of flame and the luminance temperature. The simplified two-color method reported in this paper can be used as a tool for the improvement of the combustion process in direct injection diesel engine.

• Journal of Korea Multimedia Society
• /
• v.17 no.11
• /
• pp.1279-1285
• /
• 2014

In this paper, we propose on image encryption method which uses NC(Non-linear Cycle) and 2D CAT(Two-Dimensional Cellular Automata Transform) in sequence to encrypt medical images. In terms of the methodology, we use NC to generate a pseudo noise sequence equal to the size of the original image. We then conduct an XOR operation of the generated sequence with the original image to conduct level 1 NC encryption. Then we set the proper Gateway Values to generate the 2D CAT basis functions. We multiply the generated basis functions by the altered NC encryption image to conduct the 2nd level 2D CAT encryption. Finally, we verify that the proposed method is efficient and extremely safe by conducting an analysis of the key spatial and sensitivity analysis of pixels.

• Journal of the Semiconductor & Display Technology
• /
• v.10 no.1
• /
• pp.113-118
• /
• 2011

This paper proposes computer visual inspection algorithms for PCB defects which are found in a manufacturing process. The proposed method can detect open circuit and short circuit on bare PCB without using any reference images. It performs adaptive threshold processing for the ROI (Region of Interest) of a target image, median filtering to remove noises, and then analyzes connected components of the binary image. In this paper, the connected components of circuit pattern are defined as 6 types. The proposed method classifies the connected components of the target image into 6 types, and determines an unclassified component as a defect of the circuit. The analysis of the original target image detects open circuits, while the analysis of the complement image finds short circuits. The machine vision inspection system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.4
• /
• pp.530-536
• /
• 2021

Since the LBP algorithm has the characteristic of local texture expression, it is possible to obtain completely different results depending on the extraction location and the size of the reference image and the sample image. In order to solve these shortcomings, in this paper, we first investigate the basic characteristics of LBP, make the size of the reference image (100×100) in order to include most of the characteristics in the image, and select a sample image (40×40) extracted from an arbitrary point. After finding the matching position in the LBP of the reference image by using the correlation test between the LBP of the reference image and the LBP of the sample image, a chi analysis method is used to find the reference image that most closely matches the sample image.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.5
• /
• pp.690-695
• /
• 2014

This paper presents a modified CCI image interpolation method based on the even-odd decomposition (EOD). The CCI method is a well-known technique to interpolate images. Although the method provides better image quality than the linear interpolation, its complexity still is a problem. To remedy the problem, this paper introduces analysis on the EOD decomposition of CCI and then proposes a reduced CCI interpolation in terms of complexity, providing better image quality in terms of PSNR. To evaluate the proposed method, we conduct experiments and complexity comparison. The results indicate that our method do not only outperforms the existing methods by up to 43% in terms of MSE but also requires low-complexity with 37% less computing time than the CCI method.

• Journal of the Korean Geotechnical Society
• /
• v.25 no.12
• /
• pp.119-130
• /
• 2009

To measure the soil deformation, two common techniques of the digital image analysis-Particle Image Velocimetry (PIV) and Digital Image Correlation (DIC)-have been used. To generally apply these techniques to the soils, the accuracy of these techniques should be evaluated under various conditions. In this study, the influence factors including the image resolution, the degree of displacement and deformation, the size of pixel subsets, and analysis techniques were analyzed. The deformation of an idealized particle assembly using the discrete element method was measured by the digital image analyses, and then the results were compared with the actual deformations. To conduct the optimal digital image analysis, various factors are systematically analyzed in terms of the degree of the displacement and the deformation.

• Journal of Korea Multimedia Society
• /
• v.10 no.7
• /
• pp.923-933
• /
• 2007

In this paper, we present a method for performance enhancement of the marker detection system by using SVM(Support Vector Machine) and LDA(Linear Discriminant Analysis). It converts the input image to a binary image and extracts contours of objects in the binary image. After that, it approximates the contours to a list of line segments. It finds quadrangle by using geometrical features which are extracted from the approximated line segments. It normalizes the shape of extracted quadrangle into exact squares by using the warping technique and scale transformation. It extracts feature vectors from the square image by using principal component analysis. It then checks if the square image is a marker image or a non-marker image by using a SVM classifier. After that, it computes feature vectors by using LDA for the extracted marker images. And it calculates the distance between feature vector of input marker image and those of standard markers. Finally, it recognizes the marker by using minimum distance method. Experimental results show that the proposed method achieves enhancement of recognition rate with smaller feature vectors by using LDA and it can decrease false detection errors by using SVM.

• Management & Information Systems Review
• /
• v.1
• /
• pp.401-412
• /
• 1997

Traditionally, classification of remote sensed image data is one of the important works for image data analysis procedure. So, many researchers have been devoted their endeavor to increasing accuracy of analysis, also, many classification algorithms have been proposed. In this paper, we propose new bands selection method for multispectral bands of remote sensed image data that use rough set theory. Using indiscernibility relations in rough sets, we show that can select the efficient bands of multispectral image data, automatically.