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Top 100 OpenCV Projects | Top OpenCV Projects

DAY 10 DESIGN

What is OpenCV

OpenCV is the huge open-source library for computer vision, machine learning, and image processing and it plays a major role in real-time operation in systems. To Identify image pattern and various features to use vector space to perform mathematical operations on these features.

It was built to provide infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products.

 

Top 100 OpenCV Projects

  1. Face Emotion Recognition using Raspberry Pi and OpenCV
  2. Text and Label Reading using Raspberry Pi and OpenCV
  3. Real time Face Detection using Raspberry Pi and OpenCV
  4. Multiple face detection using Raspberry Pi and OpenCV
  5. Moving Object Detection using Raspberry Pi and OpenCV
  6. Wildlife photography using Raspberry Pi and Open CV
  7. Automatic selfie camera using Raspberry Pi with Open CV
  8. Light sensing robot using Raspberry Pi and OpenCV
  9. Curved Lane Detection using Raspberry Pi and OpenCV
  10. Object Sorting based on color using Raspberry Pi and OpenCV
  11. Smart Navigation System for Blind People using Raspberry Pi and OpenCV
  12. Digital Art Drawing using Raspberry Pi and OpenCV
  13. Pick and Place Robot using Raspberry Pi and OpenCV
  14. Smart Receptionist using Raspberry Pi and OpenCV
  15. Smart ATM Security System using Raspberry Pi and OpenCV
  16. Sign Language Recognition using Raspberry Pi and OpenCV
  17. Counting Apples and Oranges using Raspberry pi and OpenCV
  18. Family Monitoring Robot Based using Raspberry Pi and OpenCV
  19. Electronic Voting Machine using Raspberry Pi and OpenCV
  20. Toll Management System using Raspberry Pi and OpenCV
  21. Drowsiness Detection using Raspberry Pi and OpenCV
  22. Night Vision Patrolling Robot with Sound Sensing using the Computer Vision Technology
  23. Baby Monitoring System using Raspberry Pi and Open CV
  24. Traffic Density Monitoring using Raspberry Pi and OpenCV
  25. Automatic Vehicle Detection and Billing using Raspberry Pi and OpenCV
  26. Smart Electronic Voting System Based on Biometric Identification using Raspberry Pi
  27. Secure Vehicle with Driver Assistant System using Raspberry Pi and OpenCV
  28. Face recognition and tracking for examination monitoring (digital invigilator) using Raspberry Pi
  29. Real-time Multiple Face detection using Raspberry Pi with Intel Modius Stick 2
  30. Gesture Controlled Home Automation

     

    1. Face Emotion Recognition using Raspberry Pi and OpenCV

    Face emotion recognition plays an important role in systems for measuring people’s emotions has dominated psychology by linking expressions to groups of basic emotions. These features are useful to distinguish the maximum number of samples accurately and it is based on discriminate analysis is used to classify different expressions.

    1. Text and Label Reading using Raspberry Pi and OpenCV

    The technologies are developed for physically impaired people in order to live confidently. A camera-based assistive text reading framework to help blind persons text labels and product packaging from hand-held objects in daily lives. Using text recognition algorithm will get filtered from the image and speech output and the text will be passed into the system to get an audio output.

    1. Real time Face Detection using Raspberry Pi and OpenCV

    Face detection is a type of biometric software application that can identify specific individual in a digital image by analyzing and comparing patterns. It is used for security purposes in a variety of other applications. The features are useful to distinguish the maximum number of samples accurately and it is matched with stored image samples for person verification.

     

    1. Multiple face detection using Raspberry Pi and OpenCV

    This Raspberry Pi allows to detect multiple faces which technology used in applications. By using Open CV technology in the cloud to process feature of the image which has multiple faces. It can be done by detecting face first and place landmarks on every face to confirm the face which is present in the image or video.

     

    1. Moving Object Detection using Raspberry Pi and OpenCV

    There are techniques to detect an object, Static and Dynamic from tracking the object when it is moving. The system is kept constant as static, it will capture the video by using computer vision technology and it will track the moving object. It enables camera to track the moving object using Open CV.

    1. Wildlife photography using Raspberry Pi and Open CV

    This Raspberry Pi is implemented with camera placed in the forest to capture unnoticed action of livings. It takes video with motion-based technology for storage optimization, with action-based camera to capture the image.

     

    1. Automatic selfie camera using Raspberry Pi with Open CV

    This Raspberry Pi features facilities like automatic and manual selfie-booth system, and the image can be captured using  Open CV technology. It detects and classifies each part of face and after detecting smile in the face as it captures the image.

     

    1. Light sensing robot using Raspberry Pi and OpenCV

    The Raspberry Pi system used technology by interfacing camera which monitoring the brightness to track light. It is used for surveillance as the beginners can work with  Open CV technology by using camera with Raspberry Pi.

     

    1. Curved Lane Detection using Raspberry Pi and OpenCV

    Raspberry pi is used where a simulation is implemented for the curved lane detection is done which will be applied to the video to detect curved lane. It’s an effective way which can used for self-driving and make driving automation.

    1. Object Sorting based on color using Raspberry Pi and OpenCV

    It is based on different characteristics, require different equipment for checking and separating. It is an efficient method which can sort the object based on the color. Raspberry Pi which will be connected to the USB camera and use OpenCV wrapper with python for the object sorting according to its color.

     

    1. Smart Navigation System for Blind People using Raspberry Pi and OpenCV

    Raspberry pi makes smart stick for blind people which will be embedded with ultrasonic sensor to detect the real time hurdles attached to the raspberry pi for perfect navigation for the blind people. The blind people interact with the system in voice. It provides more abundant surrounding information and more accurate navigation, and verify practicability of the newly proposed system.

    1. Digital Art Drawing using Raspberry Pi and OpenCV

    Digital art drawing through hand gestures and using a camera capturing the digital art. Each finger covered with different colors and gesture captured by camera and displays the digital art using raspberry pi. It recognizes the hand, tracks movements and provides information about hand position orientation and flux of the fingers.

    1. Pick and Place Robot using Raspberry Pi and OpenCV

    It allows identifying objects in random positions and performing the pick and place operation using an industrial robotic arm. The solution is composed by a carrying wood blocks of different dimensions, which arise randomly at the beginning of the conveyor and moving to an area where it can be picked up by the robot.

    1. Smart Receptionist using Raspberry Pi and OpenCV

    The system that Performs the work of Receptionist in an automatic manner. Open CV Algorithm is used to extract the facial features of humans. It is recorded and identify whenever the Person visited the company. The System reduces the human work and manpower.

     

    1. Smart ATM Security System using Raspberry Pi and OpenCV

    It simply knows the PIN number of any individuals; cash can be with-drawled by unauthorized persons. The system sends image with OTP as mail to the account holder as someone is trying to use ATM. If the account holder is trying to use ATM system identifies with its database, it will directly allow users to withdraw cash from an ATM.

     

    1. Sign Language Recognition using Raspberry Pi and OpenCV

    The technologies are being developed for deaf people in order to live confidently. It proposes a camera-based gesture reading framework to help persons to read text labels. The functions of each sign can be easily configurable to certain process using the hand sign which is detected using a camera and sign detection is done using OpenCV.

    1. Counting Apples and Oranges using Raspberry pi and OpenCV

    An accurate automated fruit detection and counting algorithm gives agricultural enterprises the ability to optimize and streamline their harvest process. It enables growers to estimate yield at scale across both data sets and is able to perform on highly fruits that are challenging for human to annotate.

     

    1. Family Monitoring Robot Based using Raspberry Pi and OpenCV

    It makes robot for monitoring the family activities and also to monitor the health. It ensures that the family monitoring data stored and displayed in real time, and used protocol to ensure that remote control and safety reliability of the robot.

     

    1. Electronic Voting Machine using Raspberry Pi and OpenCV

    The Raspberry Pi is a method of placing all necessary electronics for running a computer on a single chip. It needs an Operating system to start up. Each voting machine is locked by finger print access module. As the user is identified finger print will be sent to a specific machine for voting.

     

    1. Toll Management System using Raspberry Pi and OpenCV

    The implementation of electronic toll collection allows vehicles to travel at low or full speed during the toll payment, which help to avoid the traffic delay at toll booth. It is one type of vehicle classification system which adopts as the input sensing device for the system. It includes the development of an image-based vehicle classification system as an effort to seek for a robust vision-based vehicle classification system.

     

    1. Drowsiness Detection using Raspberry Pi and OpenCV

    Drowsiness detection system with external vehicle intrusion dodging primarily based conception. The development of such systems encounters many difficulties related to fast and proper recognition of a driver’s fatigue symptoms. One of the technical possibilities to implement driver drowsiness detection systems is to use the vision-based approach.

    1. Night Vision Patrolling Robot with Sound Sensing using the Computer Vision Technology

    It proposes a security patrolling robot that uses night vision camera for securing any premises. The robotic vehicle moves at particular intervals and is equipped with night vision camera and sound sensors. A fully autonomous security robot that operates tirelessly and patrols large areas on its own to secure the facility.

     

    1. Baby Monitoring System using Raspberry Pi and Open CV

    This idea to design a Smart Cradle System which will help to monitor child and detect every activity of the Baby. It is an innovative, smart and protective Cradle System to nurture an infant in an efficient way. A Health Algorithm is applied to these datasets to get information about the body conditions which is helpful as any regular symptoms of a disease can be identified easily.

     

    1. Traffic Density Monitoring using Raspberry Pi and OpenCV

    It focuses on the algorithm for switching the traffic lights according to vehicle density on the road and aim at reducing the traffic congestion on roads which will help lower the number of accidents. This provides safe transit for people and reduce fuel consumption. It will also provide significant data which will help in future road planning and analysis.

    1. Automatic Vehicle Detection and Billing using Raspberry Pi and OpenCV

    It aims to design and develop a new efficient toll collection system which will be a good low-cost alternative among all other systems. In this system, a camera captures images of vehicles passing through toll booths and is detected through camera. This information is passed to the Raspberry pi which is having a web server set up on it. It accesses the web server information and according to the type of the vehicle, an appropriate toll is charged.

     

    1. Smart Electronic Voting System Based on Biometric Identification using Raspberry Pi

    It is to reduce the defrauding of manual voting system which includes many steps for verification to ensure the reliability of the device. The EVM is uniqueness and consistency over time, fingerprint and facial recognition used for identification over time and it made secured. It is faster, efficient, reliable, error free and easy to operate which reduces the chances of errors.

     

    1. Secure Vehicle with Driver Assistant System using Raspberry Pi and OpenCV

    Driver assisting systems are systems which are developed to automate, adjust and improve vehicle systems for safety and better driving. The automatic system which is provided to the vehicle is proven to reduce road accidents, by reducing the human error.

     

    1. Face recognition and tracking for examination monitoring (digital invigilator) using Raspberry Pi

    The face recognition is for the automatic attendance of students in the classroom environment without intervention. It is recorded by using a camera attached in the classroom which captures images of students, detect the faces in images and compare the detected faces with the student database and mark the attendance.

     

    1. Real-time Multiple Face detection using Raspberry Pi with Intel Modius Stick 2

    It uses Intel Modius Neural compute stick takes the whole computational process makes the application to be real-time with more efficient with the high frame rate. To accelerate the frame rate with high computational power, Intel Modius neural compute stick is used, which makes the application more efficient by processing in Raspberry Pi.

    1. Gesture Controlled Home Automation

    Gesture provides a non-verbal communication using words or sounds. It enhances the user experience and simplicity in its handling. The easier mechanisms that will improve their experience in controlling home devices.

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