movement detection from likith cgppt.pptx

movement detection

1. MYSURU ROYAL INSTITUTE OF TECHNOLOGY COMPUTER SCIENCE AND ENGINEERING COMPUTER GRAPHICS AND IMAGE PROCESSING [PCC21CS63] MINI PROJECT TOPIC: MOVEMENT DETECTION Submitted by: Submitted to: Thanushree H M[4MU21CS081] Ms.Dhanya K N Thrisha K P[4MU21CS084] Assistance professor Dept.of CSE ,MRIT

2. CONTENTS 1 .Abstract 2.Introduction 3.Objective 4.Design 5.Requirement specification 6.Snapshots 7.Conclusion 8.References

3. ABSTRACT This presentation introduces a basic motion detection system using OpenCV, a popular computer vision library. The system captures live video from a webcam, processes consecutive frames to detect motion, and highlights motion areas in real-time. Key steps include computing the absolute difference between frames, converting to grayscale, applying Gaussian blur, thresholding to create a binary image, and dilating to enhance motion areas. Contours are detected and filtered to highlight significant motion with bounding rectangles. The processed video stream is displayed in a resizable window, running until the 'q' key is pressed.

4. INTRODUCTION The Motion Detection Project using OpenCV explores fundamental techniques in computer vision to detect and highlight motion in real-time video streams. This project captures live video from a webcam, processes the video frames to identify areas of motion, and visualizes these areas by drawing bounding rectangles around them. The core functionality involves several key steps: capturing consecutive frames, computing the absolute difference between them to detect changes, converting the difference image to grayscale applying Gaussian blur to reduce noise.

5. OBJECTIVE Real-Time Motion Detection Frame Differencing Noise Reduction Binary Image Creation Contour Detection and Filtering Motion Visualization User Interface Practical Application Educational Value

6. DESIGN Start program Initialize video Capture Capture Initial Frames Set up Display Window(Resizable) Processing loop Continue processing Release video capture and destroy windows End

7. REQUIREMENT SPECIFICATION Hardware Requirements: Processor : Intel Core i3 RAM : Minimum 4 Gb or 8Gb. Resolution : Minimum 640x480 Frame Rate : Minimum 15 fps ,higher frame 30fps rate for real time processing. Software Requirements: Operating System : Windows XP onwards Libraries and Tools : Python : Version 3.6 OpenCV : Version 4.x NumPy : Version 1.18 IDE: PyCharm

8. SNAPSHOTS Snapshot of movement detection

9. SNAPSHOT OF NO MOVEMENT DETECTION

10. CONCLUSION The motion detection system efficiently tracks and highlights motion by comparing consecutive video frames, suitable for real-time surveillance. The system provides dynamic visualization with bounding rectangles and status messages on the video feed, offering clear and immediate feedback. It features a user-friendly interface with a resizable video window . The adaptable contour area threshold minimizes false positives by reacting only to significant motion, enhancing reliability.

11. REFERENCES Google [https://medium.com] Wikipedia https ://youtube.com

12. THANK YOU