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OBJECT SPEED DETECTION FROM A VIDEO SCENE

 

TITLE OBJECT SPEED DETECTION FROM A VIDEO SCENE.
AUTHOR KAWEEPAP KONGKITTISAN
DEGREE MASTER OF SCIENCE PROGRAMME IN COMPUTER SCIENCE
FACULTY FACULTY OF SCIENCE
ADVISOR CHOMTIP PORNPANOMCHAI
CO-ADVISOR DAMRAS WONGSAWANG
 
ABSTRACT
The idea of using a video camera to detect the speed of a moving object has been proposed to improve the current speed detection approach, which is mostly based on radar equipment. No matter how much the technology has developed, as long as the equipment is still based on radar, there will be obvious disadvantages such as the difficulty of installation, the high cost, and the problem of interference. This research intends to develop the speed detection system using image processing. Overall works are the software development of a system that requires a video scene, which consists of the following components: moving object, starting reference point and ending reference point. The system is designed to detect the position of the moving object in the scene and the position of the reference points and calculate the speed of each static image frame from the detected positions. The Object Speed Detection From A Video Scene system consists of six major components: 1) Image Acquisition, for collecting a series of single images from the video scene and storing it in the temporary storage. 2) Image Enhancement, to improve some characteristics of the single image in order to provide more accuracy and better future performance. 3) Image Segmentation, to perform the object position detection using image differentiation. 4) Image Analysis, to analyze the position of the reference starting point and the reference ending point, using thresholding technique. 5) Speed Detection, to calculate the speed of each object in the single image frame using the detection object position and the reference point positions. 6) Report, to convey the information to the end user as readable information. The experimentation has been done in order to assess three qualities: 1) Usability, to prove that the system can determine object speed under the specific conditions laid out. 2) Performance, and 3) Effectiveness. The results show that the system works with highest performance at 320x240 resolution. It takes around 70 seconds to detect a moving object in a video scene. The system has an accuracy of 85%.
KEYWORD SPEED DETECTION/ FRAME DIFFERENTIATION STOCK

 

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