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Face recognition system

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ShitanshuRanjanSriva2

This document describes an automatic attendance system using face recognition. It discusses the following: 1. The system was created by a team of 4 students to automate attendance taking and save faculty time. It uses OpenCV and face detection algorithms. 2. The system works by training on images of students taken from the class and stored in the database. It then detects faces in new images or video and identifies the students to mark attendance. 3. Key technologies used include OpenCV for image processing, Tkinter for the GUI, Pandas and NumPy for data handling, and algorithms like Haar Cascade and LBPH for face detection and recognition.

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Automatic Attendance System By Face Recognition Supervised by :- Rajesh Pal Sir Submitted By:- Shitanshu Ranjan Srivastava [17-IEC-041] Aniruddh Singh [17-ICS-008] Ashwani kumar kushwaha [17/IEC/012] Himanshu Kumar Singh [R16-IEC-015]
Table Of Content 01 – OUR TEAM 02 – INTRO TO OUR PROJECT 03 - WORKING MODULE 04 - DEMONSTRATION
OUR TEAM Shitanshu Ranjan Srivastava [17- IEC-041] Ashwani Kumar Kushwaha [17- IEC-012] Aniruddh Singh [17-ICS- 008] Himanshu Kumar Singh [R16-IEC-015]
BASICS WE SHOULD KNOW – 1. What do you mean by facial recognition ? 2. Which model have we used for face detectiom ? 3. Why has been OpenCV used ? 4. Which algorithm has been used ? 5. How to increase the accuracy of face recognition ? 6. What is the role of tkinter in this face recognition ?
• The project is made to automate the student’s attendance overhead by faculty and save time for lectures as well. • It will also reduce the proxy of attendance to some extent. Not sure to reduce to 100% until it’s implemented. • The project is made in python using open CV (Open Source Computer Vision Library). • The software will take images of students in database in jpeg format and this dataset will be trained and detected to identify that particular student. • The images can either be took from a class video or directly through webcam as per convenience of faculty. Introduction:-
This Photo by Unknown author is licensed under CC BY-NC-ND. VS code • Visual Studio Code is a free source-code editor made by Microsoft for Windows Open CV • It is an image and video processing library with bindings in C, C++, python and java. It will be used for our facial detection Pandas • Pandas is the most popular python library that is used for data analysis. It provides highly optimized performance with back- end. NumPy • NumPy is a python library used for working with arrays. It also has functions for working in domain of linear algebra, Fourier transform, and matrices OpenpyXL • Openpyxl is a Python library for reading and writing Excel files. The openpyxl module allows Python program to read and modify Excel files. Tkinter • : Tkinter is the standard GUI library for Python. Python when combined with Tkinter provides a fast and easy way to create GUI applications. Tkinter provides a powerful object- oriented interface to the Tk GUI toolkit. TOOLS and LIBRARIES USED:-
The Algorithim has four stages Haar Feature Selection Creating Integral Images Adaboost Training Casading Classifirers Detection :- Detection is done by the help of OpenCV and Haas cascades This Photo by Unknown author is licensed under CC BY-SA.
Detection : Detection is done by using HAAR CASCADE Algorithm. The detection of face is done by clicking on attendance button on portal interface. ON clicking the attendance button Web-cam or any integrated Camera gets open to capture the images. All the sample data of only face is taken and stored in the folder training images in the root folder of project. The haar -Cascade feature allows to only capture facial images and that is converted into Grey scale by using fuction of opencv2 library imported in our project. Gray= cv2.cvtColor(img, cv2.Color_BGR2GRAY) To train faces We will be using haarcascade_frontalface_default.xml file
Haar Cascade Working:
Recognition OpenCV has three built in face recognizers and thanks to OpenCV's clean coding, you can use any of them by just changing a single line of code. Below are the names of those face recognizers and their OpenCV calls. 1. Eigen Faces Face Recognizer - cv2.face.createEigenFaceRecognizer() 2. Fisher Faces Face Recognizer -cv2.face.createFisherFaceRecognizer() 3. Local Binary Patterns Histograms (LBPH) Face Recognizer - cv2.face.createLBPHFaceRecognition Local Binary Pattern (LBP) is a simple yet very efficient texture operator which labels the pixels of an image by thresholding the neighborhood of each pixel and considers the result as a binary number. In our project we will use Recognition by LBPH recognizer
Face recognition system
Face recognition system
Local binary patterns histograms (LBPH) Face Recognizer Process • We know that Eigenfaces and Fisher faces are both affected by light and, in real life, we can't guarantee perfect light conditions. LBPH face recognizer is an improvement to overcome this drawback. • Take a 3×3 window and move it across one image. At each move (each local part of the picture), compare the pixel at the center, with its surrounding pixels. Denote the neighbors with intensity value less than or equal to the center pixel by 1 and the rest by 0. • After you read these 0/1 values under the 3×3 window in a clockwise order, you will have a binary pattern like 11100011 that is local to a particular area of the picture. When you finish doing this on the whole image, you will have a list of local binary patterns. • Now, after you get a list of local binary patterns, you convert each one into a decimal number using binary to decimal conversion (as shown in above image) and then you make a histogram of all of those decimal values. A sample histogram looks like this:
Face recognition system
Face recognition system
Face recognition system
Face recognition system
•ON clicking on attendance button the Camera window pops up. •The window opens on the same screen and recognizes the face for marking attendance •On pressing button ‘q’, the attendance gets marked.
Face recognition system
Manage record in Excel files by GUI • By the help of GUI CRUD operations can be performed in excel files Tkinter and openpyxl. • With help of Tkinter we can make GUI which purpose is to insert record in excel sheet. • With the help of OpenPyxl we will access it. • We will use pandas to convert xlsx to • csv(Comma Separated Values) file for • convenience to code and for machine to understand.
Train Image
• •We will use pandas to convert xlsx to csv(Comma Separated Values) file for convenience to code and for machine to understand. • •The student details are being entered automatically in excel sheet one who registers them from GUI directly.
DEMONSTRATON
Face recognition system
THANK YOU...

More Related Content

Face recognition system

  • 1. Automatic Attendance System By Face Recognition Supervised by :- Rajesh Pal Sir Submitted By:- Shitanshu Ranjan Srivastava [17-IEC-041] Aniruddh Singh [17-ICS-008] Ashwani kumar kushwaha [17/IEC/012] Himanshu Kumar Singh [R16-IEC-015]
  • 2. Table Of Content 01 – OUR TEAM 02 – INTRO TO OUR PROJECT 03 - WORKING MODULE 04 - DEMONSTRATION
  • 3. OUR TEAM Shitanshu Ranjan Srivastava [17- IEC-041] Ashwani Kumar Kushwaha [17- IEC-012] Aniruddh Singh [17-ICS- 008] Himanshu Kumar Singh [R16-IEC-015]
  • 4. BASICS WE SHOULD KNOW – 1. What do you mean by facial recognition ? 2. Which model have we used for face detectiom ? 3. Why has been OpenCV used ? 4. Which algorithm has been used ? 5. How to increase the accuracy of face recognition ? 6. What is the role of tkinter in this face recognition ?
  • 5. • The project is made to automate the student’s attendance overhead by faculty and save time for lectures as well. • It will also reduce the proxy of attendance to some extent. Not sure to reduce to 100% until it’s implemented. • The project is made in python using open CV (Open Source Computer Vision Library). • The software will take images of students in database in jpeg format and this dataset will be trained and detected to identify that particular student. • The images can either be took from a class video or directly through webcam as per convenience of faculty. Introduction:-
  • 6. This Photo by Unknown author is licensed under CC BY-NC-ND. VS code • Visual Studio Code is a free source-code editor made by Microsoft for Windows Open CV • It is an image and video processing library with bindings in C, C++, python and java. It will be used for our facial detection Pandas • Pandas is the most popular python library that is used for data analysis. It provides highly optimized performance with back- end. NumPy • NumPy is a python library used for working with arrays. It also has functions for working in domain of linear algebra, Fourier transform, and matrices OpenpyXL • Openpyxl is a Python library for reading and writing Excel files. The openpyxl module allows Python program to read and modify Excel files. Tkinter • : Tkinter is the standard GUI library for Python. Python when combined with Tkinter provides a fast and easy way to create GUI applications. Tkinter provides a powerful object- oriented interface to the Tk GUI toolkit. TOOLS and LIBRARIES USED:-
  • 7. The Algorithim has four stages Haar Feature Selection Creating Integral Images Adaboost Training Casading Classifirers Detection :- Detection is done by the help of OpenCV and Haas cascades This Photo by Unknown author is licensed under CC BY-SA.
  • 8. Detection : Detection is done by using HAAR CASCADE Algorithm. The detection of face is done by clicking on attendance button on portal interface. ON clicking the attendance button Web-cam or any integrated Camera gets open to capture the images. All the sample data of only face is taken and stored in the folder training images in the root folder of project. The haar -Cascade feature allows to only capture facial images and that is converted into Grey scale by using fuction of opencv2 library imported in our project. Gray= cv2.cvtColor(img, cv2.Color_BGR2GRAY) To train faces We will be using haarcascade_frontalface_default.xml file
  • 10. Recognition OpenCV has three built in face recognizers and thanks to OpenCV's clean coding, you can use any of them by just changing a single line of code. Below are the names of those face recognizers and their OpenCV calls. 1. Eigen Faces Face Recognizer - cv2.face.createEigenFaceRecognizer() 2. Fisher Faces Face Recognizer -cv2.face.createFisherFaceRecognizer() 3. Local Binary Patterns Histograms (LBPH) Face Recognizer - cv2.face.createLBPHFaceRecognition Local Binary Pattern (LBP) is a simple yet very efficient texture operator which labels the pixels of an image by thresholding the neighborhood of each pixel and considers the result as a binary number. In our project we will use Recognition by LBPH recognizer
  • 13. Local binary patterns histograms (LBPH) Face Recognizer Process • We know that Eigenfaces and Fisher faces are both affected by light and, in real life, we can't guarantee perfect light conditions. LBPH face recognizer is an improvement to overcome this drawback. • Take a 3×3 window and move it across one image. At each move (each local part of the picture), compare the pixel at the center, with its surrounding pixels. Denote the neighbors with intensity value less than or equal to the center pixel by 1 and the rest by 0. • After you read these 0/1 values under the 3×3 window in a clockwise order, you will have a binary pattern like 11100011 that is local to a particular area of the picture. When you finish doing this on the whole image, you will have a list of local binary patterns. • Now, after you get a list of local binary patterns, you convert each one into a decimal number using binary to decimal conversion (as shown in above image) and then you make a histogram of all of those decimal values. A sample histogram looks like this:
  • 18. •ON clicking on attendance button the Camera window pops up. •The window opens on the same screen and recognizes the face for marking attendance •On pressing button ‘q’, the attendance gets marked.
  • 20. Manage record in Excel files by GUI • By the help of GUI CRUD operations can be performed in excel files Tkinter and openpyxl. • With help of Tkinter we can make GUI which purpose is to insert record in excel sheet. • With the help of OpenPyxl we will access it. • We will use pandas to convert xlsx to • csv(Comma Separated Values) file for • convenience to code and for machine to understand.
  • 22. • •We will use pandas to convert xlsx to csv(Comma Separated Values) file for convenience to code and for machine to understand. • •The student details are being entered automatically in excel sheet one who registers them from GUI directly.