2. Introduction
● Closed-circuit television video surveillance (CCTV) has become more
prevalent as a result of technological advancements and the ever-increasing
need for security.
● The introduction of Artificial Intelligence continually increases sophistication
to technologies that simplify contemporary living standards and relatively, it
also has been found to play a rather important role in security and security-
based systems.
● The video surveillance market is also further expected to grow at an annual rate
of more than 10% through 2026 according to a survey.
● In accordance with this, the project proposes the development of a security
system that incorporates suspicious person detection using web cameras.
3. Abstract
● Thus, the proposed system, on the whole, is mainly developed with the
objective of being a security & precautionary measure to deter crimes.
● Through the home security system, any person who is captured within the
video frame is detected and recognised familiar or unfamiliar.
● If the person is unfamiliar and they are found to be present for a specific period
of time that is considered suspicious, then they are treated as a threat.
● An email alert is then sent to the resident/client who is logged in with the
system, along with the intruder’s image.
4. Related works
● Several contributions have been made over the years regarding security and
the most common improvisation using a surveillance camera was the
addition of an alert system.
● And this alert is sent in numerous ways: an SMS message, WhatsApp
message or an immediate call to quickly alert the owner.
● Another system has been suggested where the precise location of the
abnormality is identified and highlighted. The system transmits these images
over IOT to enable users to observe it online.
5. • The project involves incorporating the concept of deep learning.
• This section can be illustrated mainly as below, initially with the algorithm
behind the training model.
• In this project model CNN is used for implementation.
• Convolutional neural networks have advanced, and as a result of their improved
performance in competitions, they have become the subject of research.
• A Convolutional neural network (CNN)is a type of artificial neural network that
has one or more convolution layers and are used mainly for image processing,
classification, segmentation and also for other auto correlated data.
Methodology
6. • The benefit of using CNNs is their ability to develop an internal representation
of a two- dimensional image. This allows the model to learn position and scale
of faces in an image. After train the CNN it can able to recognize face in an
image One can effectively use Convolutional Neural Network for Image data.
Feature Learning, Layers, and Classification
• A CNN is composed of an input layer, an output layer, and many hidden layers in
between.These layers perform operations that alter the data with the intent of
learning features specific to the data. Three of the most common layers are :
• Convolution
• Rectified linear unit (ReLU)
• Pooling
7. ● Alexnet has 8 layers. The first 5 are convolutional and the last 3 are fully
connected layers. In between we also have some ‘layers’ called pooling and
activation.
● AlexNet is an incredibly powerful model capable of achieving high accuracies on
very challenging datasets.
Image Capturing
● When the user is not authorized, then the image will be captured and sent to the
owner through a mail. The owner can view the image from the database.
● The owner can either register the detected person for verification or deny and
declare as unauthorized .
8. Proposed Implementation
● The proposed study implements a
simple interface to add users
● An alert will be sent to the owner
about the stalker along with their
image for the resident/user to follow
any precautionary measures.
9. ● The training and testing data set is categorized of which the training data
constitutes 70% while the rest aggregates to a total of 30%.
● Further, a CNN model is developed with the essential layers and the training data
is fed to make predictions.
● The convolutional and downsampled layers of CNN are constructed by using the
convolution function and downsampling function in opencv to process the
pictures.
● One of the architecture used in CNN model is AlexNet architecture.
10. Detection of familiar face Detection of unknown face Storing unknown face with time
Experimental Results
12. Conclusion
• In this paper, we have proposed a home security system using CNN and opencv.
• Due to CNN’s capacity to spot patterns in images, a convolutional neural network
(CNN) is a type of artificial neural network that is mostly used for image
recognition and processing. The security system accurately recognizes the
authorized user i.e the resident from the given data by using CNN.
• The main focus of our project is to detect unauthorized individuals i.e the stalkers
around the house and to alert the user or resident through a mail.
13. Future Scope
• Our future work is concentrated on building our system with frequency detection
of the unidentified person, that is to notify the user about the frequency or number
of visits of the unauthorized individual in the camera.
• And to further add an alarm to alert the user in case of theft, robbery and the
stalker’s movement are at night time.The user is notified of the potential danger.
