scholarly journals Digitalization of Human Head Anthropometry Measurement Using Pixels Measurement Method

2019 ◽  
Vol 2 (3) ◽  
pp. 63
Author(s):  
Fandy Surya Pratama ◽  
Istianah Muslim ◽  
Muhammad Ihsan Zul
Keyword(s):  
Feature Extraction ◽  
Standard Deviation ◽  
Measurement Method ◽  
Digital Camera ◽  
Human Head ◽  
Data Retrieval ◽  
Safety Factors ◽  
Measuring Devices ◽  
Dimension Measurement ◽  
Ip Camera

Head Anthropometry is a part of anthropometry that needed to be measured carefully. It is because human head becomes an important part that necessary to be protected. The protection aims to look after the safety of the human head. Safety factors can be achieved by designing head products. Therefore, head anthropometry data is required to make a product design Currently, data retrieval of head anthropometry is still using several measuring devices such as anthropometers, sliding callipers, spreading callipers, and tape gauges. This measurement method makes the standard deviation become higher and also take a lot of time to capture huge amounts of anthropometry data. However, the problem has been resolved by other study research with building a head dimension measurement system using digital camera. But the system still need the integration with digital camera. This study uses the IP Camera that has been integrated with the system to capture human head from the front and side. The captured image is segmented into several areas based on head dimension. Then, the image is processed using pixel measurement method by performing feature extraction on each head dimension to get the result of head dimension measurement. The result shows that calliper measurement and system measurement against ten of fourteen human head anthropometry dimensions is identical with the best distance between IP Camera and the head as far as 200 cm. This head anthropometry data is expected to make a contribution to Indonesian Ergonomics Society.

scholarly journals Eyeglass Frame Identification Using Pixel Measurement Method and k-NN Algorithm

2017 ◽  
Vol 9 (4) ◽  
pp. 429
Author(s):  
Muhammad Ihsan Zul ◽  
Istianah Muslim ◽  
Atiya Karimah
Keyword(s):  
Feature Extraction ◽  
Digital Image ◽  
Measurement Method ◽  
Binary Image ◽  
Ip Camera

Eyeglasses have a variety of types and shapes recently. The shape of the eyeglasses frames are rectangular, square, oval, pilot, round, geometric, and wrap. This study proposed an approach them to recognize the shape of eyeglasses. The digital image becomes an important part of this research. Eyeglasses image is taken from IP Camera and other sources (internet). The image should be processed into grayscale, then convert it to the binary image to get the height and width of the eyeglasses. The height and width were used to perform feature extraction. It generates 6 attributes, 3 ratios of glasses height and 3 ratios of eyeglasses width. That six attributes are classified by the k-NN algorithm. Based on the tests performed the accuracy reaches around 58% - 71%

Detection and Analysis of Rats’ Bioelectromagnetic Signal

2014 ◽  
Vol 536-537 ◽  
pp. 13-17
Author(s):  
Hong Long Cao ◽  
Fen Ju Qin ◽  
Xue Guan Liu ◽  
He Ming Zhao
Keyword(s):  
Standard Deviation ◽  
Automatic System ◽  
Measurement Method ◽  
Measurement Accuracy ◽  
Biological Activities ◽  
Measurement Data ◽  
Measured Data ◽  
The Mean ◽  
Frequency Window ◽  
Window Effects

In this paper, we designed an automatic system and automatic test software, and they can carry out Kunming rats bioelectromagnetic measurement in standard status and anesthesia automatically in anechoic chamber where the electromagnetic field outside is shielded, the reflection wave is absorbed, and the measurement accuracy will be improved. We get a great number of measurement data with frequency-sweep measurement method. The mean and standard deviation of amplitudes vs. frequencies is calculated and analyzed. The results show the measurement method is feasible. We have plotted the means of measured data as multiple sets of Y values in a series of bars with standard deviations bars included and distributed in the frequency axis of X. It is found that the fluctuation of the mean and standard deviation in some frequencies is not evident which may explain frequency window effects, while in other frequencies, such a fluctuation can be obviously observed, which may suggest that bioelectromagnetic signal is influenced by biological activities (standard and anaesthesia status) in these frequency points.

scholarly journals Head Detection Based on DR Feature Extraction Network and Mixed Dilated Convolution Module

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1565
Author(s):  
Junwen Liu ◽  
Yongjun Zhang ◽  
Jianbin Xie ◽  
Yan Wei ◽  
Zewei Wang ◽  
...  
Keyword(s):  
Neural Network ◽  
Feature Extraction ◽  
Transmission Rate ◽  
Pedestrian Detection ◽  
Human Head ◽  
Detection Rates ◽  
Translational Invariance ◽  
Dilated Convolution ◽  
Head Detection ◽  
Small Targets

Pedestrian detection for complex scenes suffers from pedestrian occlusion issues, such as occlusions between pedestrians. As well-known, compared with the variability of the human body, the shape of a human head and their shoulders changes minimally and has high stability. Therefore, head detection is an important research area in the field of pedestrian detection. The translational invariance of neural network enables us to design a deep convolutional neural network, which means that, even if the appearance and location of the target changes, it can still be recognized effectively. However, the problems of scale invariance and high miss detection rates for small targets still exist. In this paper, a feature extraction network DR-Net based on Darknet-53 is proposed to improve the information transmission rate between convolutional layers and to extract more semantic information. In addition, the MDC (mixed dilated convolution) with different sampling rates of dilated convolution is embedded to improve the detection rate of small targets. We evaluated our method on three publicly available datasets and achieved excellent results. The AP (Average Precision) value on the Brainwash dataset, HollywoodHeads dataset, and SCUT-HEAD dataset reached 92.1%, 84.8%, and 90% respectively.

scholarly journals The Forecasting Residual Life of Corroding Pipeline based on Semi-Probabilistic Method

2010 ◽  
Vol 1 (2) ◽  
pp. 1-6 ◽  
Author(s):  
Noor N.M. ◽  
Yahaya N. ◽  
Ozman N.A.N ◽  
Othman S.R.
Keyword(s):  
Standard Deviation ◽  
Residual Life ◽  
Probabilistic Method ◽  
Time To Failure ◽  
Operating Pressure ◽  
Safety Factors ◽  
Internal Corrosion ◽  
Maintenance Schedule ◽  
Operating Strategies ◽  
Pipeline Failures

In general, the prediction of pipeline residual life can effectively assist pipeline operators to evaluate future safe operating strategies including re-inspection and appropriate maintenance schedule. As a result it can minimize the possibility of pipeline failures until it reaches its designed lifetime. A semi-probabilistic methodology for predicting the remaining strength of submarine pipelines subjected to internal corrosion based on Recommended Practice RP-F101 by Det Norske Veritas (DNV) is described in this paper. It is used to estimate the maximum allowable operating pressure of the corroding pipelines based on series of pigging data, which represents corrosion pit location and dimension. The introduction of partial safety factors in the DNV code to minimise the effect of uncertainties due to the defect sizing has improved the reliability of pipeline assessment methodology. Nevertheless, the code is still regarded as a fully deterministic approach due to its incapability of predicting the remaining life of corroded pipeline. Thus, we have added prediction capabilities to the capacity equation by introducing a standard deviation model of future defect depth. By doing so, the variation of safety factors of the capacity equation can be fully manipulated in which prediction of future pipeline residual life becomes feasible. The paper demonstrates calculation and prediction of pipeline residual life subjects to internal corrosion. The results shows the standard deviation of corrosion parameter affected the value of partial safety factor as corrosion progressing, hence amplify the conservatism of time to failure.

HISTOGRAM OF TRANSITION FOR HUMAN HEAD RECOGNITION

2016 ◽  
Vol 78 (5-9) ◽  
Author(s):  
Panca Mudjirahardjo ◽  
M. Fauzan Edy Purnomo ◽  
Rini Nur Hasanah ◽  
Hadi Suyono
Keyword(s):  
Feature Extraction ◽  
Color Image ◽  
Recognition Rate ◽  
Orientation Angle ◽  
Human Head ◽  
Input Image ◽  
Foreground Extraction ◽  
Multi Scale ◽  
Novel Method ◽  
Main Component

The main component for head recognition is a feature extraction. One of them as our novel method is histogram of transition. This feature is relied on foreground extraction. In this paper we evaluate some pre-processing to get foreground extraction before we calculate the histogram of transition.We evaluate the performance of recognition rate in related with preprocessing of input image, such as color, size and orientation. We evaluate for Red-Green-Blue (RGB) and Hue-saturation-Value (HSV) color image; multi scale of 10×15 pixels, 20×30 pixels and 40×60 pixels; and multi orientation angle of 315o, 330o, 345o, 15o, 30o, and 45o.For comparison, we compare the recognition rate with the existing method of feature extraction, i.e. Histogram of Oriented Gradients (HOG) and Linear Binary Pattern (LBP). The experimental results show Histogram of Transition robust for changing of color, size and orientation angle.

scholarly journals Design and development of a novel acoustic rain sensor with automated telemetry

2018 ◽  
Vol 201 ◽  
pp. 03003
Author(s):  
Maria Leonora Guico ◽  
Gemalyn Abrajano ◽  
Prince Aldrin Domer ◽  
Jose Paulo Talusan
Keyword(s):  
Low Cost ◽  
Data Retrieval ◽  
Mobile Internet ◽  
Time Interval ◽  
Time Data ◽  
Tropical Regions ◽  
Recorded Sound ◽  
Measuring Devices ◽  
The Impact ◽  
Initial Results

This paper presents the recent results of the design of a novel acoustic rainfall sensing system that is low-cost, portable, and easily deployable, which makes use of the recorded sound produced by the impact of the raindrops on the sensor surface. The sensor design allows the gathering of acoustic signal power and sending it to a server after a specified time interval, either through SMS or mobile internet connection. It exists in a weather-proof, standard-conformant, standalone system with its own power supply and telemetric capabilities. These acoustic point sensors can gather rainfall data at high spatial and temporal resolutions. Such deployments can show the variations of rainfall intensities in sub-kilometer areas, particularly in the tropical regions. Since it is low-cost, it can also improve the density of rainfall measuring devices in an area. Moreover, the reliability is improved by providing near-real time data, as opposed to tipping buckets with manual data retrieval. The prototype sensor system was placed next to standard rain measuring devices and observed during the rainy season. The paper will discuss the design and deployment of the system, as well as initial results of data analysis and comparison with standard rain measuring devices.

Matrix Based Feature Measurement and Extraction for Face Recognition

2015 ◽  
Vol 738-739 ◽  
pp. 643-647
Author(s):  
Qi Zhu ◽  
Jin Rong Cui ◽  
Zi Zhu Fan
Keyword(s):  
Principal Component Analysis ◽  
Feature Extraction ◽  
Face Recognition ◽  
Measurement Method ◽  
Principal Component ◽  
Component Analysis ◽  
High Accuracy ◽  
Face Image ◽  
Two Dimensional ◽  
The Matrix

In this paper, a matrix based feature extraction and measurement method, i.e.: multi-column principle component analysis (MCPCA) is used to directly and effectively extract features from the matrix. We analyze the advantages of MCPCA over the conventional principal component analysis (PCA) and two-dimensional PCA (2DPCA), and we have successfully applied it into face image recognition. Extensive face recognition experiments illustrate that the proposed method obtains high accuracy, and it is more robust than previous conventional face recognition methods.

3D Digitization of Human Body Based on Checkerboard Matching

2013 ◽  
Vol 718-720 ◽  
pp. 1108-1112
Author(s):  
Jian Li ◽  
Cheng Yan Zhang ◽  
Xue Li Xu ◽  
Hai Feng Chen
Keyword(s):  
Feature Extraction ◽  
Body Size ◽  
Human Body ◽  
Measurement Method ◽  
Stereo Matching ◽  
Low Cost ◽  
Size Measurement ◽  
Body Images ◽  
General Application ◽  
3D Digitization

A body-size measurement method based on checkerboard matching is proposed. First, calibrated cameras are used to acquire two body images after projecting chess boards on human body with projector. Then, the parallax of the two images is got by feature extraction and stereo matching. Finally, we can calculate the 3D coordinates of the human body according to the principle of binocular vision to complete the acquisition of body size. The result shows that measurement error is ± 4%. This study can measure automatically and improve precision compared with traditional methods while it has low-cost, simple operation compared with the non-contact measurement. And the results accuracy can meet its general application in practice.

scholarly journals Analisis Citra Kuning Telur Berbasis Ekstraksi Ciri Statistika Orde Satu untuk Mengenali Jenis Telur Ayam Ras dan Ayam Kampung

eLEKTRIKA ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 74
Author(s):  
Muhammad Sipan ◽  
Rony Kartika Pramuyanti
Keyword(s):  
Feature Extraction ◽  
Standard Deviation ◽  
Egg Yolk ◽  
Mean Value ◽  
First Order ◽  
Free Range ◽  
Chicken Egg ◽  
Egg Yolks ◽  
Native Chickens ◽  
Chicken Eggs

<p><em>Chicken eggs are one of the most familiar side dishes in Indonesia besides tempeh. High protein and low prices make eggs a favorite side dish for the people of Indonesia. Although almost every day we see egg yolks we often can't tell for sure what chicken egg yolks we see. Based on this, the author tries to study egg yolk imagery based on first-order feature extraction using various features such as variance, skewness, carding, entropy, and mean. Statistical calculations are used based on the pixel values of the original image in this first-order texture calculation with the sole purpose of finding the histogram properties of the image. The results of first-order statistical characteristic calculations were used to differentiate between native and purebred chicken eggs. This study facilitates decision making, especially in the selection of accurate and measurable egg yolks from several types of chicken eggs, thereby minimizing public mistakes in choosing eggs based on egg yolks. The first step that can be done is to determine the data consisting of various types of images of free-range chicken egg yolks. These are free-range chicken eggs and purebred chicken eggs. The image is then segmented by separating the yolk and white, then first-order statistical analysis which later the results of these statistical calculations can be used as a reference in determining the type of egg. The results of the trial resulted in first-order feature extraction statistical values, namely for native chickens, the mean value was 132.743, min 69.5255, max 252.5, standard deviation was 29.922 and variance was 905.882. The average value of statistics was order 1 for native chickens. of mean 137,176, min 48, max 240.2, standard deviation 31,454 and variance of 957.89.</em></p>

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