Electrocardiogram (ECG) is a widely used tool for the early diagnosis and evaluation of cardiac disorders. The ECG signal is usually distorted during recording by different types of noise which may lead to incorrect diagnosis. Therefore, clear ECG signals are required to support good cardiac disorder diagnosing. In this paper, an efficient ECG denoising method using combined discrete wavelet with Savitzky-Golay (S-G) filter is proposed. The performance of S-G filter is studied in terms of polynomial degree and frame size, i.e. signal section. In addition, the performance of denoising wavelet is studied in term of mother wavelet type and wavelet order. The advantage of S-G filter is combined with discrete wavelet denoising method to get better denoising performance. The performance of denoising ECG are evaluated using signal to noise ratio (SNR) and percentage root mean square difference (PRD). For this we used simulated and gaussian white noise surrogated ECG signals. Our results show that combined S-G and wavelet filter denoising is noticeable better than the respective individual procedures. In addition, we found that the selection of frame size, order of the S-G filter and the wavelet type and order should be done carefully in order to get optimal results. It also holds true for the new filter that the optimal choice of filter parameters is a compromise between noise reduction and distortion.
Detecting the level of the liquid is very essential for any chemical study in research labs. The objective of this paper is to design real-time liquid level detection system using image processing. Besides, this system is able to indicate the color of the liquid during chemical reaction. The proposed system was developed using vision assistant tools in LabVIEW and webcam. Regarding to webcam resolution, the average accuracy of the system is approximately 99%.
Smart parking system becomes essential nowadays specially in urban area because it can reduce the time and the fuel wasted in searching for an empty parking slot. The aim of this paper is to develop smart parking system based on improved Optical Character Recognition (OCR) model. The proposed system consists of three stages: 1) OCR based parking slot detection, 2) User notification based on IoT approach, 3) Smart parking meter based on Simple Mail Transfer Protocol (SMTP). In this system, the vacant parking slots are detected using improved OCR model by labeling the parking slots with specific characters. The system identifies empty parking slots by detecting these characters with installed camera above the parking slots, otherwise the parking slots are occupied. The performance of the proposed OCR model in detecting these characters is enhanced by considering two stages of advanced morphology filter to remove unwanted small/large objects from the image. The accuracy of the proposed OCR model is tested by eight images having different parking street textures as a background and characters written with seven font styles. The idea of detecting empty parking spaces is to share the number of vacancies on a website for the drivers searching for a parking space. However, a time-controlled parking system with different charge rate each hour can be considered to make the best utilization of parking spaces available in urban areas. Therefore, a smart parking meter is proposed to notify the user through Email about the time left that allowed to be parked and the change in charge rate. The proposed system is developed and implemented using vision assistant of LabView.
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