Density Based Smart Traffic Control Using Canny Edge Detection Algorithm

Abstract

Background: The project which is entitled as density based smart traffic control system using canny edge detection algorithm for congregating traffic information deals with problem of urban traffic congestion.As the population in the urban areas increasing there is a necessity for a effective and smart traffic control system using advanced and latest technology and equipment to improve the traffic control.The current methods for controlling traffic are timers or human control are proved to be ineffective as the traffic is increasing rapidly.In this project we are developing a method where the time is allocated according to the measure of the vehicle density using canny edge detection with digital image processing is proposed.This imposing traffic control system offers great improvement in response time, vehicle management, automation, reliability and overall efficiency over the existing systems.To implement this technique we are uploading the current traffic image to the application and application will extract edges from images and if there is more traffic then there will be more number of edges with white color and if the uploaded image contains less traffic then it will have less number of white color edges.

Objectives:

Malicious attacks are increasing day by day though many techniques are used to avoid them.

DDoS attacks are the major threats these days.

We are proposing an approach to detect those attacks by using co-clustering algorithm

Methods:

1.Data preparation

In this method modern-day site visitors photograph could be uploaded to the machine after which convert shadeation photograph into Gray Scale photograph layout to have pixels values as black and white shadeation.

1. Image analyzing

In this method Gaussian Filter may be implemented on uploaded pix to transform the photograph into clean format. After making use of the clear out out Canny Edge Detection may be implemented at the photograph to get the rims from the photograph. Images are preprocessed.

1. white pixel count module

we can be counted number white pixels from a canny photograph to get whole visitors be counted number. After side detection, the ensuing pics are binary photograph with most effective black and white pixels

1. Calculate Green Signal Time Allocation

Based on white pixel count traffic signal time will be Allotted

Conclusions: In this venture an powerful visitors manage machine availing picture processing as an device for measuring the density has been proposed. Besides explaining the constraints of contemporary close to useless visitors manage machine, the blessings of the state-of-the-art visitors manage machine had been explained. For this venture, pattern snap shots of various visitors situation can be provided. After of of entirety of side detection, the similarity among pattern snap shots with the reference picture can be analysed.