Real Time Facial Recognition System

Ashwini, .; Balaji, Vijay; Srinivasan, Srivarshini; Monisha, Kavya

doi:10.1007/978-3-030-41862-5_175

Cited by 1 publication

(1 citation statement)

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“…The OpenCV code hopes to be an inexpensive, accurate, and fast processing colorimetry analysis method that enables the determination of pollutant concentration. Previous study proven that OpenCV can be implemented in various field, commonly for real-time face recognition, for automated attendance system [18][19] [20] This paper will examine the development of the openCV code for measuring NH3 parameter with reference to the Phenate Standard Method based on SNI 06-6989.30-2005 and color parameter by referring to the Standard Method (APHA, 2005). This study is currently at the preliminary stage, focusing on the constructing the algorithm of openCV code , and factors which affect the results in terms of linearity, background conditions during image collection, factors that influence the Pt-Co sample image measurement process by using OpenCV-Python, which then will be taken into account in further research progress.…”

Section: Introductionmentioning

confidence: 99%

The Utilization OpenCV to Measure the Water Pollutants Concentration

Syah¹,

Hakiki²

2021

j.environ.eng.waste.manag.

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Abstract. Intensive water quality determination needs to be adjusted with technological developments to meet today's society's needs and increased water pollution due to urbanization. Therefore, early detection is essential for in site water quality determination and as a critical consideration in making health and environmental decisions. OpenCV is a library programming feature for Computer Vision which focuses on extracting information from images in real-time, this can be considered to be potential to measure the pollutant concentration. Objectives: This study identify the potential of colorimetry analysis method by using OpenCV as an alternative method for pollutant concentration measurement. Method and results: First stage, this study collecting the data of NH3 phenate and Pt-Co CU from the spectrophotometer. The first stage also was including the development of an OpenCV code. Then, the data was collected were processed to get the concentration of NH3 and Pt-Co both using OpenCV and spectrophotometer; factors that influence the Pt-Co sample image measurement process by using OpenCV-Python was analyzed too. Then in the analysis stage, the result of the two measurement method was tested by statistic determine its significant difference. The conclusion found whether OpenCV could be potential to measure the pollutant concentration or not. Conclusion: the OpenCV has potential to be use as alternative colorimetry measurement method to determine water pollutant as there is no significant difference in the spectrophotometric method results and the results from OpenCV for Pt-Co sample. Meanwhile, in this study found that the result of NH3 from spectrophotometer is nonlinear different with from OpenCV that is linear. Thus, further research is needed to test the validity of OpenCV method. The factor influence of measurement using OpenCV code is when determining the Region of Interest (ROI) and determining the pixel values for the normalized box filter

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Section: Introductionmentioning

confidence: 99%