Computer Vision Projects for Final Year

Byadmin Project Ideas

Computer Vision Projects for final year students and the latest project ideas for BSc, BS, BE, BEng, MSc, MS, BCA, MCA, BTech and MTech. These Computer Vision projects play an important role in a student’s final year learning. These projects help students understand real applications and apply technical concepts in a practical way. Choosing the right Computer Vision project also improves practical knowledge and builds confidence for future careers.

Computer Vision Projects for Final Year

Latest Computer Vision Project Ideas

  1. Human Detector and Counter using Python
    This project is used to find and count people in images, videos, or live webcam footage. The user uploads media, and the system automatically detects human presence. It helps in areas like crowd monitoring and safety analysis. The focus is only on detecting people, not on what they are doing.
  2. Face Recognition Attendance System
    This project is a smart attendance system that uses face recognition to mark when people arrive. It takes a photo of each person, saves it, and matches it the next time they enter. If someone is late, the system gives a voice warning. It helps save time and keeps attendance secure.
  3. Image Blurring & Deblurring With Noise Removal
    This project is about editing images in an easy way. It lets a user blur and unblur pictures using different visual effects. The user can also add noise to an image and remove it to make the image look clearer. The original image can be restored and saved with the selected effects.
  4. Image Steganography Using Kmeans & Encryption
    This project hides secret messages inside an image so no one can easily notice them. The image is first divided into small parts to place the hidden data safely. The hidden message is also locked using a secret code for extra safety. This makes sharing sensitive information more secure.
  5. Yoga Poses Detection using OpenPose
    This project helps people practice yoga correctly using a computer and a camera. It looks at a photo or live video and recognizes the yoga pose being performed. The system then shows the name of the pose and helps the user understand their posture. This allows users to practice yoga safely even without a trainer.
  6. Bone Fracture Detection using Python
    This project creates a system that can automatically detect bone fractures from X-ray images. A user can upload an X-ray, and the system highlights the broken area. This helps doctors quickly identify fractures without errors or delays. It also allows hospital admins to manage patient and hospital records efficiently.
  7. Currency Detector App for Visually Impaired
    This project is a mobile app that helps visually impaired people identify paper money. The user can speak a command to open the phone camera, take a picture of a note, and the app will tell them the value using voice. It uses technology to understand speech commands and read the currency aloud. The app recognizes different notes by analyzing their images with machine learning.
  8. Student Attendance with Fingerprint Reader
    This project is a smart attendance system for schools and colleges using fingerprint scanning. Each student marks their attendance by placing their finger on the reader, which checks it against stored records. The system automatically records attendance, generates reports, and lists students who are absent. It makes tracking attendance simple and reduces manual work for teachers.
  9. Dental Caries Detection System using Python
    This project is a smartphone-based system that can detect dental caries from a photo uploaded by the user. It uses artificial intelligence to check if a tooth has decay or not. The system is easy to use and saves people from visiting a dental clinic. It can help more people get timely dental examinations, especially where regular checkups are costly.
  10. Hand Gesture Recognition Project
    This project is about recognizing hand gestures using images. The system can count how many fingers are shown in a picture. It first finds the hand in the image and then processes it to detect individual fingers. Finally, it shows the finger count to the user accurately.
  11. Bone Fracture Detection System
    This project is about creating a system that can detect broken bones from X-ray images automatically. It cleans the X-ray images to remove noise and makes them clearer. Then it tracks the bones and identifies fractures by type. The system shows a box around the fracture and helps doctors detect broken bones more quickly and accurately.
  12. Traffic Signal: Management & Control System
    This project is a smart traffic signal system that helps control traffic at a four-way junction. It measures how busy each road is and changes the signal timings so that the busiest roads move first. The system shows traffic levels with simple graphics and can also give priority to emergency vehicles like ambulances. This makes traffic flow smoother and reduces waiting times for everyone.
  13. Fingerprint Based ATM System
    This project is a Fingerprint Based ATM system that allows users to access their bank account using their fingerprint instead of an ATM card. Each person’s fingerprint is unique, making the system safer and more secure. Users can check their balance, withdraw money, transfer funds, and view recent transactions easily. It removes the need to carry an ATM card and prevents fraud.
  14. Object Tracker Based on Color
    This project is about tracking objects in a video based on their colors. The system can find red, green, and blue objects in real time. It cleans up the video frames to remove unwanted parts and then highlights the colored objects with a rectangle. This helps to follow and monitor objects automatically.
  15. Detect Irregular moving objects and tracking based on color and shape in real-time
    This project detects and follows moving objects in a live video based on their color and shape. It uses a webcam to capture video frames and finds objects of a chosen color. The system tracks the largest object and shows its position on the screen. Users can change the color to detect different objects in real time.
  16. Video Surveillance Project
    This project builds a smart video surveillance system that watches an area continuously but records only when something unusual happens. It can detect events like theft, fire, or unwanted movement after hours. When an incident is found, the system alerts the user immediately. It sends a message and an image so quick action can be taken while saving storage space.
  17. Dental Caries Detection System
    This project system helps find tooth decay using dental images. The images are cleaned to remove noise so the damaged areas can be seen clearly. The system then checks each tooth image and highlights decay if it is present. This reduces manual effort and helps dentists make faster decisions.
  18. Symbol Recognition Using Matlab
    This project is about recognizing symbols from images using MATLAB. The user gives a symbol image, and the system processes it to identify the symbol. The image is converted to black and white for better accuracy, compared with stored symbol templates, and the result is shown as text. The system uses basic image processing and optical character recognition to detect symbols with around 60 to 80 percent accuracy.
  19. Facial Expression Recognition
    This project can detect a person’s facial expression and identify if they are happy, sad, or surprised. The system first looks at the person’s face and measures features like the eyes and lips. Then it compares these features with standard expressions to understand the emotion. The software can also recognize the person and show their details.
  20. Image Character Recognition Using Signal & Pattern Analysis
    This project focuses on reading text from images. It takes pictures of typed, handwritten, or printed text and converts them into machine-readable text. The system cleans the image, removes noise, and identifies each character. It then matches the characters with stored patterns and displays the recognized text.
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