WinVMDS integrated with neural recognition windows-based video motion detector system integrated with neural recognition

WinVMDS Integrated with Neural Recognition is a neural network-based recognition system in which the main object is to create a microprocessor-based system for building or home security. The system is divided into several modules. The Ultrasonic Module is responsible for detection thereby sending a...

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Main Authors: Ang, Rosalinda C., Cruz, Maria Corina L., Tan, Lilybeth U., Yap, Maria Paula R.
Format: text
Language:English
Published: Animo Repository 1994
Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/16595
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etd_bachelors-171082021-12-04T02:21:14Z WinVMDS integrated with neural recognition windows-based video motion detector system integrated with neural recognition Ang, Rosalinda C. Cruz, Maria Corina L. Tan, Lilybeth U. Yap, Maria Paula R. WinVMDS Integrated with Neural Recognition is a neural network-based recognition system in which the main object is to create a microprocessor-based system for building or home security. The system is divided into several modules. The Ultrasonic Module is responsible for detection thereby sending a signal to trigger the system. When and if triggered, the video camera captures the image. The image captured and a pre-captured image, that is an image of the plain background, passes through the Feature Extraction Module to extract the image that triggered the system. Hereafter, the image extracted is prepared for input to the neural network by the Image Enhancement module. The resulting image is stored in a file of 1's and 0's representing the black and white pixels respectively. The file, before being entered into the main recognition module is segmented into 100 divisions, a procedure adapted to compress and convert the image into an acceptable form. The Neural Recognition Module then determine if the initially captured image exhibits a form of a human being. If the image triggers a yes in the neural recognition module, the Siren Module is triggered. The system was trained on 50 training sets equally divided to the different orientations of the human body and non-human images. Increase in the number of training sets and decrease in acceptable error would lessen the probability of the neural recognition module in bringing about an error. 1994-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/16595 Bachelor's Theses English Animo Repository
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
description WinVMDS Integrated with Neural Recognition is a neural network-based recognition system in which the main object is to create a microprocessor-based system for building or home security. The system is divided into several modules. The Ultrasonic Module is responsible for detection thereby sending a signal to trigger the system. When and if triggered, the video camera captures the image. The image captured and a pre-captured image, that is an image of the plain background, passes through the Feature Extraction Module to extract the image that triggered the system. Hereafter, the image extracted is prepared for input to the neural network by the Image Enhancement module. The resulting image is stored in a file of 1's and 0's representing the black and white pixels respectively. The file, before being entered into the main recognition module is segmented into 100 divisions, a procedure adapted to compress and convert the image into an acceptable form. The Neural Recognition Module then determine if the initially captured image exhibits a form of a human being. If the image triggers a yes in the neural recognition module, the Siren Module is triggered. The system was trained on 50 training sets equally divided to the different orientations of the human body and non-human images. Increase in the number of training sets and decrease in acceptable error would lessen the probability of the neural recognition module in bringing about an error.
format text
author Ang, Rosalinda C.
Cruz, Maria Corina L.
Tan, Lilybeth U.
Yap, Maria Paula R.
spellingShingle Ang, Rosalinda C.
Cruz, Maria Corina L.
Tan, Lilybeth U.
Yap, Maria Paula R.
WinVMDS integrated with neural recognition windows-based video motion detector system integrated with neural recognition
author_facet Ang, Rosalinda C.
Cruz, Maria Corina L.
Tan, Lilybeth U.
Yap, Maria Paula R.
author_sort Ang, Rosalinda C.
title WinVMDS integrated with neural recognition windows-based video motion detector system integrated with neural recognition
title_short WinVMDS integrated with neural recognition windows-based video motion detector system integrated with neural recognition
title_full WinVMDS integrated with neural recognition windows-based video motion detector system integrated with neural recognition
title_fullStr WinVMDS integrated with neural recognition windows-based video motion detector system integrated with neural recognition
title_full_unstemmed WinVMDS integrated with neural recognition windows-based video motion detector system integrated with neural recognition
title_sort winvmds integrated with neural recognition windows-based video motion detector system integrated with neural recognition
publisher Animo Repository
publishDate 1994
url https://animorepository.dlsu.edu.ph/etd_bachelors/16595
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