Efficient Implementation of Mean, Variance and Skewness Statistic Formula for Image Processing Using FPGA Device

Kardian, Aqwam Rosadi; Sudiro, Sunny Arief; Madenda, Sarifuddin

doi:10.11591/eei.v7i3.687

Cited by 8 publications

(9 citation statements)

References 1 publication

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“…Tables 4 and 5 present the matrix of correlation coefficients and statistical characteristics of the RSSI data measured in Quito and Valle de los Chillos after having applied the inverse normal distribution method dividing the data with the LQI. It can be observed that the statistical characteristics in each LQI range are very small, with which the accuracy of the inverse normal distribution algorithm can be evidenced, the value that changes the most in relation to the original data is the variance, which represents the variability of a data series with respect to its mean [33]. A small decrease in the dispersion of the data found with respect to its mean is denoted, this effect was more evident in the "GOOD" range, decreasing the variance by 12.77%.…”

Section: Resultsmentioning

confidence: 99%

Description and analysis of Sigfox received signal strength indicator dataset by using statistical techniques

Lara-Cueva,

Yandún-Imbaquingo,

Bustamante-Lucio

2024

Bulletin EEI

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Low power wide area network (LPWAN) technology has expanded and is essential in the development of applications for the internet of things (IoT). The Sigfox LPWAN network is characterized by its long-range coverage, low cost and power consumption. In this article, a set of 5174 values is analyzed, containing 1606 null RSSI data, obtained with the Sipy module and MicroPython, which provide a coverage map of several points with a resolution of 200 meters deployed in Quito–Ecuador. It is evaluated the type of distribution to which the set of network measurements is adjusted and an optimal 900 MHz propagation model in suburban environments is determined from the measurements obtained from the known base station. As a result, the lost values of RSSI were predicted using the inverse normal distribution method in the original values, observing that they conform to a logistic distribution. The data from the base station were subjected to a data augmentation algorithm designed in MATLAB, determining that the stanford university interim (SUI) model reduces the precision error in the trend of the curve by not presenting changes greater than 5 dB, achieving a precision of 97% with respect to the fit of the curve of the data.

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Section: Resultsmentioning

confidence: 99%

Description and analysis of Sigfox received signal strength indicator dataset by using statistical techniques

Lara-Cueva,

Yandún-Imbaquingo,

Bustamante-Lucio

2024

Bulletin EEI

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“…Descriptive statistics, which includes Mean, Max value, Min value, Quartile or Q values-Q1, 2 or Median, and 3, Standard deviation is the most basic but highly informative statistical data mining technique to obtain enough light on the nature and distribution of any data [30]. Another important parameter is the 'Skewness' of the data [31]. It is an estimation of data distribution and its direction.…”

Section: Feature Extractionmentioning

confidence: 99%

A Study on Various Common Denoising Methods on Chest X-ray Images

Chattopadhyay¹

2022

Artificial Intelligence Evolution

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Image 'denoising' is an important pre-processing step as noise affects the image quality. The behaviors of denoising algorithms have been examined on a set of 2D Chest X-ray (CXR) images. Both the 'Linear' and 'non-Linear' denoising methods are considered, each having two techniques, such as (i) Moving average and (ii) Gaussian under the Linear method, and (iii) Median and (iv) Bilateral under the non-Linear method, respectively. Noise variance and Signal-to-Noise Ratio (SNR) are computed on the raw images. The study finds that, Median filter is the best of the lot with the PSNR mean = 34.5213; PSNR σ = 0.9618; MSE mean = 12.2337; MSE σ = 1.5491; and Big(O) = 0.02873 milliseconds. Finally, a comparative study has been made among these denoising methods to predict five hundred Tubercular CXRs, which shows that, using the Median filter, 92% CXRs can be accurately diagnosed, followed by Gaussian, Bilateral, and Moving average type filters with the respective accuracies of 80%, 72%, and 60%, respectively. This work could be a ready-reckoner to the researchers in choosing the best filtering technique when working on Medical X-ray images.

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“…the local minima or maxima of first derivative are utilized to detect the points lying on an edge as illustrated in Figure 2 [8], [16].…”

Section: First Order Edge Detectionmentioning

confidence: 99%

Lane detection system for day vision using altera DE2

2019

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The active safety systems used in automotive field are largely exploiting lane detection technique for warning the vehicle drivers to correct any unintended road departure and to reach fully autonomous vehicles. Due to its ability, to be programmed, to perform complex mathematical functions and its characterization of high speed processing, Field Programmable Gate Array (FPGA) could cope with the requirement of lane detection implementation and application. In the present work, lane detection is implemented using FPGA for day vision. This necessitates utilization of image processing techniques like filtering, edge detection and thresholding. The lane detection is performed by firstly capturing the image from a video camera and converted to gray scale. Then, a noise filtering process for gray image is performed using Gaussian and average filter. Methods from first and second order edge detection techniques have been selected for the purpose of lane edge detection. The effect of manually changing the threshold level on image enhancement has been examined. The results showed that raising threshold level would better enhance the image. The type of FPGA device used in the present work is Altera DE2. Firstly, the version DE2 Cyclone II start with (11xxxxxx-xxxx) together with Genx camera has been used. This camera supports both formats NTSC and PAL, while the above version of FPGA backups only NTSC format. The software of lane detection is designed and coded using Verilog language.

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Efficient Implementation of Mean, Variance and Skewness Statistic Formula for Image Processing Using FPGA Device

Cited by 8 publications

References 1 publication

Description and analysis of Sigfox received signal strength indicator dataset by using statistical techniques

Description and analysis of Sigfox received signal strength indicator dataset by using statistical techniques

A Study on Various Common Denoising Methods on Chest X-ray Images

Lane detection system for day vision using altera DE2

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