• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.43 no.2
• /
• pp.33-38
• /
• 2020

Anomaly detection of Machine Learning such as PCA anomaly detection and CNN image classification has been focused on cross-sectional data. In this paper, two approaches has been suggested to apply ML techniques for identifying the failure time of big time series data. PCA anomaly detection to identify time rows as normal or abnormal was suggested by converting subjects identification problem to time domain. CNN image classification was suggested to identify the failure time by re-structuring of time series data, which computed the correlation matrix of one minute data and converted to tiff image format. Also, LASSO, one of feature selection methods, was applied to select the most affecting variables which could identify the failure status. For the empirical study, time series data was collected in seconds from a power generator of 214 components for 25 minutes including 20 minutes before the failure time. The failure time was predicted and detected 9 minutes 17 seconds before the failure time by PCA anomaly detection, but was not detected by the combination of LASSO and PCA because the target variable was binary variable which was assigned on the base of the failure time. CNN image classification with the train data of 10 normal status image and 5 failure status images detected just one minute before.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.6
• /
• pp.2098-2114
• /
• 2021

Light intensity variation is one of the key factors which affect the accuracy of vehicle face re-identification, so in order to improve the robustness of vehicle face features to light intensity variation, a Nonnegative Matrix Factorization model with the constraint of image acquisition time difference is proposed. First, the original features vectors of all pairs of positive samples which are used for training are placed in two original feature matrices respectively, where the same columns of the two matrices represent the same vehicle; Then, the new features obtained after decomposition are divided into stable and variable features proportionally, where the constraints of intra-class similarity and inter-class difference are imposed on the stable feature, and the constraint of image acquisition time difference is imposed on the variable feature; At last, vehicle face matching is achieved through calculating the cosine distance of stable features. Experimental results show that the average False Reject Rate and the average False Accept Rate of the proposed algorithm can be reduced to 0.14 and 0.11 respectively on five different datasets, and even sometimes under the large difference of light intensities, the vehicle face image can be still recognized accurately, which verifies that the extracted features have good robustness to light variation.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.41 no.6
• /
• pp.1085-1097
• /
• 2017

In the era of new media, images hold an important position as episteme to express and convey ideas. Fashion films provide dynamic and unique fashion images, differentiated from prior fashion media as a representational tool for showing a realistic fashion image only; consequently, their production and spread are increasing rapidly as a new fashion media. This study identifies the meaning and type of fashion images in fashion films based on the concept of Deleuze's image that help discover distinctive characteristics of fashion films as a new fashion media of an expressive tool. Literature research was conducted on new media, concepts and types of images by Deleuze to analyze types of new media images. According to research, fashion image in fashion film is defined as a fashion event; consequently, three types of new media images are derived. As the result of the empirical study, fashion images in fashion films are classified by images of realistic movement, variable time, and virtual experience. The results of the consideration show that fashion films expressed fashion through temporality and narrative, senses, and diegesis. Fashion images of new media in fashion films portray fashion as a process that transcends reality and imagination.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1994.10a
• /
• pp.504-509
• /
• 1994

Recently SMT is used widely to place the SMD on bare board which is very small and highly integrated. And that is one of the issue directly in the electric products assembly process and especiallly in the field of optimizing electric product's performance, automatically tuning method which is highly demanded in the electronics industry. To tune product's performance, variable resistances's resistivity should be changed until it has good performance characteristics. In this paper to automatically regulate the 8mm camcoder's performance, it is proposed variable resistence's center position and orientation detection algorithm by image processing, which has very precise and accurate result. And we found optimal conditions which can have effects on image acquisition process. And real time processing is done by DSP to detect vr's center and orientation. This results make it possible to utilize proposed image processing algorithm and system directly in electronics industry.

• Korean Journal of Remote Sensing
• /
• v.27 no.1
• /
• pp.69-74
• /
• 2011

It may be an important issue to estimate population of a concerned country. In this study, an appropriate variable was selected to establish a model which fits best the relationship between the night time imagery of DMSP-OLS and population data. Exponential model was selected which was proposed by previous study. Accuracy validation was also performed for each variable extracted from the night time imagery of DMSP-OLS. Consequently, the model showed high accuracy when applied to the area of a certain amount of light was existed. However, further consideration should be necessary when to applied other country or other part of regions.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.1
• /
• pp.71-77
• /
• 2020

In this paper, we propose a method in which PingPong256 combines LFSR and variable clock to generate an irregular PRNG and use it for image encryption. PingPong256 is guaranteed an extended period based on the two LFSRs, and the variable clock is a structure that outputs the result of operating a predetermined clock in one operation by referring to the state of the different LFSR. A variable clock is characterized by the difficulty of predicting the output at any time because the choice increases with time. PingPong256 combines the advantages of LFSR and variable clock, the convenience of hardware and software implementation, and the benefits of sensitivity and irregular periods. Also, the statistical safety was verified using the NIST SP800-22, the safety of the proposed method, and the sensitivity of the image change was tested using NPCR and UACI.

• Journal of the Korean Society of Radiology
• /
• v.10 no.4
• /
• pp.263-270
• /
• 2016

This paper suggests techniques to enhance coding time which is a problem in traditional fractal compression and to improve fidelity of reconstructed images by determining fractal coefficient through adaptive selection of block approximation formula. First, to reduce coding time, we construct a linear list of domain blocks of which characteristics is given by their luminance and variance and then we control block searching time according to the first permissible threshold value. Next, when employing three-level block partition, if a range block of minimum partition level cannot find a domain block which has a satisfying approximation error, There applied to 24-bpp color image compression and image techniques. The result did not occur a loss in the image quality of the image when using the encoding method, such as almost to the color in the YIQ image compression rate and image quality, such as RGB images and showed good.

• Journal of the Korea Society of Computer and Information
• /
• v.7 no.4
• /
• pp.52-58
• /
• 2002

This Paper describes the method of real time object tracking using variable searching window. Monitoring systems require real time object tracking in video, efficiencies depend on environment of monitoring target. To get a position of object using a difference between background image and input image, the system extracts contour and centroid of the object. This method track motion of object using variable searching window from size and position of object. The background imgaes and camera are limited as fixed environment. The test result of proposed method Is 17-23FPS, this shows more fast process speed than average(10-14FPS) of existing object tracking method.

• Journal of the Korean Society of Radiology
• /
• v.8 no.7
• /
• pp.435-441
• /
• 2014

This paper suggests techniques to enhance coding time which is a problem in traditional fractal compression and to improve fidelity of reconstructed images by determining fractal coefficient through adaptive selection of block approximation formula. First, to reduce coding time, we construct a linear list of domain blocks of which characteristics is given by their luminance and variance and then we control block searching time according to the first permissible threshold value. Next, when employing three-level block partition, if a range block of minimum partition level cannot find a domain block which has a satisfying approximation error, There applied to 24-bpp color image compression and image techniques. The result did not occur a loss in the image quality of the image when using the encoding method, such as almost to the color in the RGB image compression rate and image quality, such as gray-level images and showed good.

• Korean Journal of Remote Sensing
• /
• v.34 no.6_3
• /
• pp.1351-1367
• /
• 2018

Image registration is an essential process for image fusion, change detection and time series analysis using multi-sensor images. For this purpose, we need to detect accurately the difference of scale and rotation between the multi-sensor images with difference spatial resolution. In this paper, we propose a new feature matching method using variable circular template for image registration between multi-resolution images. The proposed method creates a circular template at the center of a feature point in a coarse scale image and also a variable circular template in a fine scale image, respectively. After changing the scale of the variable circular template, we rotate the variable circular template by each predefined angle and compute the mutual information between the two circular templates and then find the scale, the angle of rotation and the center location of the variable circular template, respectively, in fine scale image when the mutual information between the two circular templates is maximum. The proposed method was tested using Kompsat-2, Kompsat-3 and Kompsat-3A images with different spatial resolution. The experimental results showed that the error of scale factor, the error of rotation angle and the localization error of the control point were less than 0.004, $0.3^{\circ}$ and one pixel, respectively.