Detect and count moving objects is a key component of automated visual
surveillance and tracking system. Formerly based detection of moving object soften use background subtraction and
frame difference are complex and take a long time. In this thesis proposal, the
authors propose a simple and fast method to detect and count moving objects
using neural networks. The main idea in neural networks is that the connections
are allowed between adjacent units only.This proposal consists of the
implementation of the basic templates available in Neural Networks. There are
some rules in neural networks that should be implemented when programming
template, such as object equations, output equations, boundary conditions and
initial values. These template sare combined to create the most ideal
algorithm to calculate the moving objects in the film. A moving object film
using the handycam. The film then segmented into images that are used to count
moving object. The algorithm used to detect and count moving objects. The
proposal also includes the use of Computer Vision Toolbox in MATLAB. The
analysis was done by comparing the position of objects in each frame according
to the time. This analysis indicates whether the object has increased or
decreased.
Keywords : Moving Object Detection; Background Subtraction; Matlab; Neural Network.ealing;
Link Download
0 komentar:
Posting Komentar