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Table of contents INTRODUCTION Background Problem Statement Scope of The Research Objective Method DESIGN SYSTEM TESTING AND EVALUATION CONCLUSION.

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Presentation on theme: "Table of contents INTRODUCTION Background Problem Statement Scope of The Research Objective Method DESIGN SYSTEM TESTING AND EVALUATION CONCLUSION."— Presentation transcript:

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2 Table of contents INTRODUCTION Background Problem Statement Scope of The Research Objective Method DESIGN SYSTEM TESTING AND EVALUATION CONCLUSION

3 INTRODUCTION Unsafe environment. A lot of work done to improve security in environment. One was by installing security cameras. The system has a weakness because only as monitoring tool. Background Problem Statement Scope of The research ObjectiveMethod

4 INTRODUCTION The problem is how to create and implement the program algorithm to detect object motion and apply it to interface with microcontroller AT89S51. Problem Statement Scope of The research ObjectiveMethodBackground

5 INTRODUCTION To build the security system using camera with image processing technology and can give warning danger like alarm sound and LED turn on by connect microcontroller type AT89S51. Problem Statement Scope of The research ObjectiveMethodBackground

6 INTRODUCTION Utilize camera webcam as security tool. To simulate the security system and can give warning if detected motion object. Problem Statement Scope of The research ObjectiveMethodBackground

7 INTRODUCTION Literature study Design algorithms to detect movement of the object. Create a design simulation using DT- Combo AVR-51 Perform testing, analysis and conclude the results based on simulation tests Problem Statement Scope of The research ObjectiveMethodBackground

8 DESIGN SYSTEM Block Diagram Flowchart

9 DESIGN SYSTEM Figure configuration on DT-Combo AVR-51

10 DESIGN SYSTEM Block Diagram Flowchart Camera acquisition Frame acquiring Subtraction frame START Detection object Find point center object Moving object Send “x” Send “y” A A microcontroller END T Y T Y

11 TESTING AND EVALUATION TestingEvaluation Figure : Sample image not detected object

12 TESTING AND EVALUATION TestingEvaluation Figure : Sample images which detected object

13 TESTING AND EVALUATION TestingEvaluation Figure : Sample image before detection object without light Figure : Sample image after detection object without light

14 TESTING AND EVALUATION TestingEvaluation Testing of Illumination

15 TESTING AND EVALUATION TestingEvaluation Testing of distance object

16 TESTING AND EVALUATION TestingEvaluation Output of microcontroller response Output microcontroller if detection object Output microcontroller if not detection object

17 TESTING AND EVALUATION TestingEvaluation  Object detected is marked with a square showing the area detected object. Further movement of the object will be detected with these markers.  Objects can be detected in morning and evening condition as well as because the condition have enough light intensity from sun. At night condition without light, camera can not detect moving object. And can detect moving object enhance of light.  Object can be detected up to distance of 6 m from the camera, while on 6.5 m object distance is no longer detectable.

18 TESTING AND EVALUATION TestingEvaluation  All of them conducted if the result response detected object then output of the microcontroller are buzzer give sound and LED turn on. If response not detected object, the output only display turn on LED.  Response time also influence on the object distance of camera. The response detect in computer is very slow. Because farther the distance objects from the camera, the more longer response required.

19 1.The system can be running in simulate accordance with objective of thesis. 2.Object detection depends on light intensity, to get good quality perform, need enough lighting condition to detect objects. The system can not work properly if intensity of light in the room is less or nothing. 3.Object distance of camera also affects the working of the system. In this system, maximum distance that can detect objects as far as 6 m. 4. Average time delay needed in this experiment result is 3.6 second. Increasingly the distance objects from the camera, the more longer than response required of system. CONCLUSION

20 1. The system has been implemented using a algorithm based on frame differencing and dynamic template matching shown to be quite accurate and effective in detection object even underbad lighting condition. 2. The system can be improve algorithm to detection specific object. 3. FPGA can be utilized as alternate from microcontroller for perform motion detection system with quickly. Suggestion

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