Age and Gender Detection Using Python and opencv

Devarinti Venumadav; T.Lavanya

Age and Gender Detection Using Python and opencv

Authors: Devarinti Venumadav, T.Lavanya

Unique Paper ID: 175787
Volume: 11
Issue: 11
PageNo: 5026-5031

Keywords: Face detection OpenCV Haar Cascade Video surveillance Security purpose etc.

Abstract:
The project aim is used to predict the age and gender of the person who was coming in front of the camera. An growing number of applications, especially after the increase in social networks and social media, are being concerned with automatic age classification. It is used to estimate a person's age and gender from a facial image using deep learning techniques. The system should be capable of working in real-time applications for security, marketing, and human-computer interaction. The proposed system aims to improve accuracy compared to traditional methods. In this project, we leverage Deep Learning and Computer Vision techniques to develop an Age and Gender Detection system using OpenCV and Convolutional Neural Networks (CNN). The system analyzes facial images to predict gender (Male/Female) and categorize individuals into predefined age groups. By utilizing CNN for feature extraction and a pre-trained Caffe model for classification, we achieve improved accuracy in age and gender prediction. The system is capable of real-time detection and has applications in security, marketing, human-computer interaction, and surveillance. The implementation focuses on efficient facial feature extraction, reducing computational complexity while maintaining high classification accuracy. The primary programming language used for this project is Python, due to its extensive support for machine learning and deep learning libraries. OpenCV is utilized for image processing and face detection, allowing efficient real-time detection of facial features. For classification, a Convolutional Neural Network (CNN) is implemented, enabling the model to accurately predict age and gender. Additionally, Haar Cascade Classifiers are employed for face detection, leveraging pre-trained models to identify human faces in images and video streams. This combination of technologies ensures high accuracy and performance in the detection process. In this project, we have successfully implemented an Age and Gender Detection system using Deep Learning and OpenCV. By utilizing Convolutional Neural Networks (CNN) and a pre-trained Caffe model, the system effectively identifies gender and estimates age from facial images. The model demonstrates reliable accuracy in classification while operating in real-time, making it suitable for applications such as security surveillance, marketing, and human-computer interaction

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 11
PageNo: 5026-5031

Age and Gender Detection Using Python and opencv

Available:https://ijirt.org/Article?manuscript=175787

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