• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2003.06a
• /
• pp.82-85
• /
• 2003

This paper proposes a preprocessing method for tracking aircraft's take-off and lading. The method uses accumulative difference image technique for segmenting the object from the background, and obtains the centroid of the object exactly using centroid method. Then the moving object is analyzed and represented with the information such as feature point, velocity, and distance. A simulation result reveals that the proposed algorithm has good performance in segmenting and tracking the aircraft.

• Proceedings of the KIEE Conference
• /
• 2001.11c
• /
• pp.459-460
• /
• 2001

In this paper, we analyze algorithms for diagnosing of VEP(visual evoked potential) signal. We used wavelet transform for the preprocessing of VEP signal data and back propagation neural network for the pattern recognition. We used several wavelets to study their effects and efficiency in the preprocessing of VEP. The diagnosis system led to good results. We obtained the noise reduced and compressed signal with the wavelet transform of the training VEP signal. So it is possible to train the neural network faster and exact diagnosis processing is possible in the neural network. From the experimental results, we know that the discrimination ability of the neural network is changed by the type of basis vector and the proposed system is good to the diagnosis of VEP.

• Journal of Biomedical Engineering Research
• /
• v.22 no.3
• /
• pp.285-291
• /
• 2001

In this paper, we designed two preprocessing adaptive filter - high pass filter and notch filter - using FPGA. For minimizing the calculation load of multi-channel and high-resolution ECG system, we utilize FPGA rather than digital signal processing chip. To implement the designed filters in FPGA, we utilize FPGA design tool(Altera corporation, MAX-PLUS II) and CSE database as test data. In order to evaluate the performance in terms of processing time, we compared the designed filters with the digital filters implemented by ADSP21061(Analog Devices). As a result, the filters implemented by FPGA showed better performance than the filters based on ADSP21061. As a consequence of examination, we conclude that FPGA is a useful solution in multi-channel and high-resolution signal processing.

• Journal of Korean Institute of Industrial Engineers
• /
• v.37 no.4
• /
• pp.400-407
• /
• 2011

Modeling and analysis of high-dimensional spectral data provide an opportunity to uncover inherent patterns in various information-rich data. Orthogonal signal correction (OSC) a preprocessing technique has been widely used to remove unwanted variations of spectral data that do not contribute to prediction or classification. In the present study we propose a novel OSC algorithm called adjusted direct OSC to improve visualization and the ability of classification. Experimental results with real mass spectral data from condom lubricants demonstrate the effectiveness of the proposed approach.

• Journal of the Korean Society of Industry Convergence
• /
• v.26 no.5
• /
• pp.785-792
• /
• 2023

Because hyperspectral imaging provides detailed spectral information across a broad range of wavelengths, it can be utilized in numerous applications, including environmental monitoring, food quality inspection, medical diagnosis, material identification, art authentication, and crime scene analysis. However, hyperspectral images often contain various types of distortions due to the environmental conditions during image acquisition, which necessitates the proper removal of these distortions through a data preprocessing process. In this study, a preprocessing method was investigated to effectively correct the distortion caused by artificial light sources used in indoor hyperspectral imaging. For this purpose, a halogen-tungsten artificial light source was installed indoors, and hyperspectral images were acquired. The acquired images were then corrected for distortion using a preprocessing that does not require complex auxiliary equipment. After the corrections were made, the results were analyzed. According to the analysis, a statistical transformation technique using mean and standard deviation with reference to a reference signal was found to be the most effective in correcting distortions caused by artificial light sources.

• Journal of the Institute of Convergence Signal Processing
• /
• v.23 no.4
• /
• pp.249-255
• /
• 2022

Potholes are an important clue to the structural defects of asphalt pavement and cause many casualties and property damage. Therefore, accurate pothole detection is an important task in road surface maintenance. Many machine learning technologies are being introduced for pothole detection, and data preprocessing is required to increase the efficiency of deep learning models. In this paper, we propose a preprocessing method that emphasizes important textures and shapes in pothole datasets. The proposed preprocessing method uses intensity transformation to reduce unnecessary elements of the road and emphasize the texture and shape of the pothole. In addition, the feature of the porthole is detected using Superpixel and Sobel edge detection. Through performance comparison between the proposed preprocessing method and the existing preprocessing method, it is shown that the proposed preprocessing method is a more effective method than the existing method in detecting potholes.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.6
• /
• pp.79-85
• /
• 2019

Recently, small radar require the development of small millimeter wave radar with high distance resolution to disable the target's system with a single strike. Small millimeter wave radar with high distance resolution need to process large amounts of data in real time to acquire and track target. In this paper, we summarized the real-time data preprocessing method to process the large amount of data required for small millimeter wave radar. In addition, the digital IF(Intermediate Frequency) receiver, Window processing, and, DFT(Discrete Fourier Transform) functions presented by real-time data preprocessing are implemented using FPGA(Field Programmable Gate Array). Finally the implemented real-time data preprocessing module was applied to the signal processor for small millimeter wave radar and verified by performance test related to the real-time preprocessing function.

• The Journal of the Acoustical Society of Korea
• /
• v.41 no.6
• /
• pp.629-636
• /
• 2022

We present a preprocessing method for an underwater target detection model based on a convolutional neural network. The acoustic characteristics of the ship show ambiguous expression due to the strong signal power of the low frequency. To solve this problem, we combine feature preprocessing methods with various feature scaling methods and spectrogram methods. Define a simple convolutional neural network model and train it to measure preprocessing performance. Through experiment, we found that the combination of log Mel-spectrogram and standardization and robust scaling methods gave the best classification performance.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.27 no.12
• /
• pp.1800-1809
• /
• 1990

This paper proposed a preprocessing algorithm which is named Automatic Tracking Window (ATW), which eliminates the effects of noises at spatial signals and spurious peaks at high-resolution algorithm in bearing estimation algorithm. This method estimates spatial spectrum by periodogram algorisdthm and hihg-resolution algorithm after preprocessing of spatial signal by automatically tracked window.

• Journal of the Institute of Convergence Signal Processing
• /
• v.14 no.2
• /
• pp.90-94
• /
• 2013

Research for Manchu character digitalization is at an early stage. This paper proposes a preprocessing algorithm for Manchu character recognition. This algorithm improves the existing Hilditch thinning algorithm so that it corrects thinning error for Manchu characters. The existing algorithm separates the characters into the left-hand side and right-hand side, while our alogorithm uses the central point between the points that strokes exist when it classifies each of characters. The experimentation results show that this method is valid for thinning and classification of Manchu characters.