• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.3
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• pp.49-58
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• 2020

Image interpolation, a technology that converts low resolution images into high resolution images, has been widely used in various image processing fields such as CCTV, web-cam, and medical imaging. This technique is based on the fact that the statistical distributions of the white Gaussian noise and the difference between the interpolated image and the original image is similar to each other. The proposed algorithm is composed of three steps. In first, the interpolated image is derived by random image interpolation. In second, we derive weighting functions that are used to apply non-local mean filtering. In the final step, the prediction error is corrected by performing non-local mean filtering by applying the selected weighting function. It can be considered as a post-processing algorithm to further reduce the prediction error after applying an arbitrary image interpolation algorithm. Simulation results show that the proposed method yields reasonable performance.

• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.3
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• pp.55-59
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• 1984

This paper describes a method of Hangout recognition using 2 - D digital filtering. The 170 patterns classified by the positions of the initial sound (consonant), middle sound (vowel) and terminal sound (consonant) of the 1,659 characters were established and models formed by using 2 - D digital filtering for each patterns were obtained. Based on these models we proposed an algorithm that can recognize KOREAN combinational characters by separating patterns from them with superpostion principles. As a result of simulation, 100% of recognition rate is obtained in the case of the print letter.

• Journal of Korea Multimedia Society
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• v.13 no.10
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• pp.1413-1422
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• 2010

With the emergence of digital TV broadcasting, various channels are provided to a TV audience. But it is getting hard for the audience to find his or her preferred TV programs due to the huge number of TV channels. In order to mitigate the difficulty, TV broadcasting companies provide an electronic program guide (EPG), which is a digital guide to scheduled broadcast TV programs. However, it results in the information overload problem and the time-consuming problem since the number of TV channels and programs is gradually on the increase. In this paper, we design and develop a channel filtering system, which recommends a small number of channels by filtering TV channels based on the watching pattern of the TV audience. The channel filtering system does not require the replacement or upgrade of existing TV or set-top box. In addition, it increases usability by skipping the channels that broadcast the audience's non-preferred TV programs while the TV audience presses the channel up/down button.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.101-108
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• 2024

AI-OCR (Artificial Intelligence Optical Character Recognition) combines OCR technology with Artificial Intelligence to overcome limitations that required human intervention. To enhance the performance of AI-OCR, training on diverse data sets is essential. However, the recognition rate declines when image colors have similar brightness levels. To solve this issue, this study employs Homomorphic filtering as a preprocessing step to clearly differentiate color levels, thereby increasing text recognition rates. While Homomorphic filtering is ideal for text extraction because of its ability to adjust the high and low frequency components of an image separately using a gamma value, it has the downside of requiring manual adjustments to the gamma value. This research proposes a range for gamma threshold values based on tests involving image contrast, brightness, and entropy. Experimental results using the proposed range of gamma values in Homomorphic filtering suggest a high likelihood for effective AI-OCR performance.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.106-112
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• 1990

This paper presents the FIR filtering scheme for digital distance protection. In most faults, there exists severe oscillation of apparent impedance according to distortion in transient waveforms. In these cases, this scheme provides more accurate fault detection and fault location, as compared with conventional schemes for digital distance protection or Kalman filtering schemes. The test of these facts were performed on EMTP result data. For the real time implementation of the proposed schemes, the motorola DSP 56001 was used to the main calculation board of the digital protective relaying system.

• Journal of Biomedical Engineering Research
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• v.15 no.3
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• pp.281-288
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• 1994

In this paper, a new decomposition method of the interference EMG signal using MAMDF filtering and digital signal processor. The efficient software and hardware signal processing techniques are employed. The MAMDF filter is employed in order to estimate the presence and likely location of the respective templates which may include in the observed mixture, and high-resolution waveform alignment is employed in order to provide the optimal combination set and time delays of the selected templates. The TMS320C25 digital signal processor chip is employed in order to execute the intensive calculation part of the software. The method is verified through a simulation with real templates which are obtain ed from needle EMG. As a result, the proposed method provides an overall speed improvement of 32-40 times.

• Proceedings of the KSR Conference
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• 2000.11a
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• pp.733-739
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• 2000

This paper is described the development of on-line partial discharge detector for high voltage apparatus. This detector consists of acoustic and high frequency current sensors, amplifier part, A/D converter part, data communication part and computer. The contents of paper are characteristics of units and digital signal processing for reducing noise in partial discharge detection. We seek methods to do good digital signal processing for detection of partial discharge. We apply digital filtering methods to the elect Tic signal and a cross con-elation to the acoustic signal. This paper shows the characteristics of these filtering method and cross con-elation in partial discharge detection.

• Transactions of the Korean Society of Automotive Engineers
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• v.1 no.3
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• pp.55-62
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• 1993

Autoregressive moving average(ARMA) model which is a time domain parametric modeling method is implemented for modeling and reproducing characteristics of exhaust noise of an automobile in various RPM range. Experiments have been carried out using 9 set of exhaust noise signals measured at 1,000-3,000 RPM range. Characteristics of sampled signals were estimated using ARMA modeling and Akaike's FPE(final prediction error) criterion to define exact model structure and for model validation. The digital filter consisted of the esitmated ARMA(70,1) model parameters was programed to reproduce exhaust noise. The spectral analysis of reproduced noise is very close to original. The results show that our approaching technique for reproducing acoustic characteristics is valid and feasible to apply in the field of noise quality control.

• Journal of Biomedical Engineering Research
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• v.10 no.1
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• pp.1-10
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• 1989

An automatic lung nodule detection algorithm was applied for digital radiographic images using Bit Slice Processor. In this algorithm, signal enhancing filtering and signal suppressing filtering were performed on the given digital chest image, respectively. Then we grit the dirt- frrence image from these filtered images, and hi-level island images were obtained by applying various threshold values. From the island images, we decided the suspicious nodules using size and circularity test, and marked them to alert radiologists. The performance of the atgorithm was analyzed with respect to the size, contrast and position of digitally synthesized nodules. This method presented 45.8% of true positive ratio for the nodules of lOw in diameter with 12-16 pixel value differnces.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.05a
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• pp.166-171
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• 2001

A digital seismic data acquisition and processing system using a PC has been developed in order to replace the analog data acquisition system of shallow marine seismic survey. An A/D converter that has 12bits of resolution and 225KHz of conversion rate was ued to acquire data, and a data acquisition software was developed as a Windows program which provides convenience of use. Raw data acquired at field has been saved to the hard-disk simultaneously. The signal to noise ratio, vertical and horizontal resolution could be improved by a digital data processing of the raw data. The digital processing of the raw data includss gain recovery, filtering, deconvolution, and muting. With the prediction deconvolution algorithm multiple reflections appearing on the shallow marine seismic section could be removed successfully.