• Journal of the Korean Society of Radiology
• /
• v.15 no.1
• /
• pp.1-7
• /
• 2021

In order to acquire an image in a positron emission tomography, it is necessary to draw the position coordinates of the scintillation pixels of the detector module measured at the same time. To this end, in a detector module using a plurality of scintillation pixels and a small number of photosensors, it is necessary to obtain a flood image and divide a region of each scintillation pixel to obtain a position of a scintillation pixel interacting with a gamma ray. Alternatively, when the number of scintillation pixels and the number of photosensors to be used are the same, the position coordinates for the position of the scintillation pixels can be directly acquired as digital signal coordinates. A method of using a plurality of scintillation pixels and a small number of photosensors requires a process of obtaining digital signal coordinates requires a plurality of photosensors and a signal processing system. This complicates the signal processing process and raises the cost. To solve this problem, in this study, we developed a method of obtaining digital signal coordinates without performing the process of separating the planar image and region using a plurality of flash pixels and a small number of optical sensors. This is a method of obtaining the position coordinate values of the flash pixels interacting with the gamma ray as a digital signal through a look-up table created through the signals acquired from each flash pixel using the maximum likelihood function. Simulation was performed using DETECT2000, and verification was performed on the proposed method. As a result, accurate digital signal coordinates could be obtained from all the flash pixels, and if this is applied to the existing system, it is considered that faster image acquisition is possible by simplifying the signal processing process.

• Journal of the Korean Society for Precision Engineering
• /
• v.13 no.6
• /
• pp.168-176
• /
• 1996

A diagnosis system which can monitor tool breakage and chipping in real time was developed using a DSP(Digital Signal Processor) board in face milling operation. AR modelling and band energy method were used to extract the feature of tool states from cutting force signals. Artificial neural network embedded on DSP board discriminates different patterns from features got after signal processing. The features extracted from AR modelling are more accurate for the malfunction of a process than those from band energy method, even though the computing speed of the former is slow. From the processed features, we can construct the real time diagnosis system which monitors malfunction by using a DSP board having a parallel processing capability.

• Journal of the Institute of Convergence Signal Processing
• /
• v.12 no.3
• /
• pp.176-180
• /
• 2011

Even though algorithms for watermark embedding and extraction step are important issue for digital watermarking, watermark selection and post-processing can give us an opportunity to improve our algorithms and achieve higher performance. For this reason, we summarized the possibilities of improvements for digital watermarking by referring to the watermark merging techniques rather than embedding and extraction algorithms in this paper. We chose Cox's function as main embedding and extraction algorithm, and multiple barcode watermarks as a watermark. Each bit of the multiple copies of barcode watermark was embedded into a gray-scale image with Cox's embedding function. After extracting the numbers of watermark, we applied the watermark merging techniques; including the simple merging, N-step iterated merging, recover merging and combination of iterated-recover merging. Main consequence of our paper was the fact of finding out how multiple barcode watermarks and merging techniques can give us opportunities to improve the performance of algorithm.

• Proceedings of the KOSOMBE Conference
• /
• v.1992 no.05
• /
• pp.175-178
• /
• 1992

This paper proposes a method called linear prediction (a high performant technique in digital speech processing) for analyzing digital ECG signals. There are several significant properties indicating that ECG signals have an important feature in the residual error signal obtained after processing by Durbin's linear prediction algorithm. The ECG signal classification puts an emphasis on the residual error signal. For each ECG's QRS complex. the feature for recognition is obtained from a nonlinear transformation which transforms every residual error signal to set of three states pulse-cord train relative to the original ECG signal. The pulse-cord train has the advantage of easy implementation in digital hardware circuits to achive automated ECG diagnosis. The algorithm performs very well feature extraction in arrythmia detection. Using this method, our studies indicate that the PVC (premature ventricular contration) detection has a at least 90 percent sensityvity for arrythmia data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.10a
• /
• pp.351-354
• /
• 2007

In recent years, digital processing techniques have been applied diversity of fields. Typical signal processing techniques are speech processing and image processing. And filters for the signal processing can be divided in FIR (finite impulse response) filter and IIR (infinite impulse response) filter. Compared with IIR filter, the FIR Filter has a defect of high-degree, but has a merit of stability and uses simply. Futhermore, FIR filter also has linear phase response characteristics, it is using in fields regarding wave information importantly. To FIR Filter design, the main issue is to remove the Gibbs phenomenon. Therefore, in this paper I was proposed a method using FIR digital filter applied a modified window function and the method was compared with conventional methods.

• Journal of IKEEE
• /
• v.26 no.2
• /
• pp.299-305
• /
• 2022

Analog-digital converter (ADC) should be one of the most important blocks that convert various physical signals to digital ones for signal processing in the digital signal domain. As most operations of the analog circuit for sensor signal processing have been replaced by digital circuits, high-resolution performance is required for ADC. In addition, low-power must be the critical issue in order to extend the battery time of mobile system. The existing integrating sigma-delta ADCs has a characteristic of high resolution, but due to its low supply voltage condition and advanced technology, circuit error and corresponding resolution degradation of ADC result from the finite gain of the operational amplifier in the integrator. Buffer compensation technique can be applied to minimize gain errors, but there is a disadvantage of additional power dissipation due to the added buffer. In this paper, incremental signal-delta ADC is proposed with buffer switching scheme to minimize current and igh-pass bias circuit to improve the settling time.

• Journal of the Korean Society of Safety
• /
• v.6 no.2
• /
• pp.21-30
• /
• 1991

In this paper, we study effect of waveness at the optical surface roughness measurement. In generally, waveness components cause errors in calculation of the roughness value of metal surface. We study about surface roughness signals In the frequency domain for separate two signal component of real roughness and waveness by digital signal processing methods. Thereafter, determine low and high Component of frequency spectrum. By this separating frequency value we design liner low and high pass filter which cutoff frequency is 1 Hz. After this process, converted each filtered spectrum by inverse discrete fourier transformation to time domain waveness and real roughness signals We calculate surface roughness value from filtered roughness signals. For evaluate this method, we use five specimens roughness signal which obtained from optical surface roughness measuring system in 3mm/s moving speed with 0.1 mm laser beam spot size As a result, we obtain more linerized roughness value than that of unfiltered roughness signals.

• International Journal of Precision Engineering and Manufacturing
• /
• v.1 no.1
• /
• pp.106-110
• /
• 2000

The researches classifying the artificial flaws in welding parts are performed using the pattern recognition technology. For this purpose the signal pattern recognition package including user defined function is developed and the total procedure is made up the digital signal processing, feature extraction, feature selection, classfier design. Specially it is composed with and discussed using the ststistical classfier such as the linear discriminant function classfier, the empirical Bayesian classfier.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.05a
• /
• pp.495-498
• /
• 2004

In the sound insulation measurements, the influence of background (extraneous) noise is often serious problem and how to reduce its effect and to improve the signal-to-noise(S/N) ratio is an important theme. As the background noise, such extraneous noises as road traffic noise and machine noise often disturb the measurement. In laboratory measurements on specimens with high sound insulation performances, even the internal noise of the measurement system can become a problem. To improve the signal-to-noise ratio and to improve the measurement accuracy, various kinds of digital signal processing techniques can be applied. In this paper, four kinds of digital signal processing techniques are applied and their effectiveness is examined by a simple sound insulation measurement.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.24 no.7
• /
• pp.730-736
• /
• 2013

Time-domain clutter generation model for airborne pulse doppler phase-array radar is presented. Time-domain surface clutter signal is generated assuming earth of a sphere and considering geometry of a clutter patch, and generation of sub-array clutter signal is presented. The generated sub-array clutter signal can be used by simulation input signal in various radar applications of DBF(Digital Beamforming), ABF(Adaptive Beamforming), Stap(Space-Time Adaptive Processing) and etc.