International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 05 | May -2017
p-ISSN: 2395-0072
www.irjet.net
Image Processing Approach to Identify and Recognize Traffic Symbols & Provide Voice Alerts Using Fuzzy Integral Snehal.P.Shinde, Sneha.M.Konade, Sonali.Y.Khenat, Devika.D.Thakar, Prof. Abhay Meshram Department of Computer Engineering, K.J. College of Engineering & Management Research,Pune. ---------------------------------------------------------------------***--------------------------------------------------------------------detected while travelling from source to destination. These symbols guide us throughout our journey. The image processing technique is widely used for this purpose. It is nothing but processing and studying the features of the various images captured.
Abstract— In today’s modern world people are using tremendous technologies so as to make there life more simpler. People are facing various issues in day to day life in which traffic plays a major role. Due to non observing traffic symbol it leads the fatal accidence which is comparatively hazardous have a system is required which automatically detects the traffic symbol and analyzes it. This paper recommended the use of various methodologies and algorithms such as block creation, block correlation, color identification, fuzzy logic and video frame creation. Most of the systems are having some performance issues that can lead to lower accuracy of the techniques so this paper proposes a novel idea of traffic symbol detection. To enhance the process of automatic traffic symbol detection and efficient image morphology our system works quite efficiently with required voice alerts.
These operations lead us to the final output where the image is captured and recognized. It makes use of the various recent algorithms for the appropriate study of the system. The traffic signs guide us to drive in a systematic manner without causing harm to living things such as animals, environment, human beings, etc. Hence the traffic signs are way important to us. Firstly the input image is captured which consist of traffic symbols. Further the images will be processed and studied in detail. The image will be divided into blocks and will be represented in a matrix form. Here the Block Creation Algorithm plays a major role. The image will be present in different blocks and further the features of the image will be studied. The next step is color identification where the consistency of the RGB will be calculated accordingly. The blocks are needed to be labelled for more accuracy. Again the edge analysis of the image is more important so as to get more accurate results.
Keywords—image block, block labeling, edge analysis, shape and symbol identification, block correlation, fuzzy logic, voice alert.
I.
INTRODUCTION
People are facing major issues in our day-to-day life. Though various solutions are confronted in order to make human life more simpler. In today’s technical world people are using different vehicles to reduce the pain of travelling from one place to another. Major accidents are taking place due to ignorance of the traffic signs and rules. As a result of increasing traffic signs, the drivers are expected to learn all the traffic signs and pay attention to them while driving. Hence a system is needed that will automatically detect and recognize the traffic signs which will comparatively ease the driving process resulting in major reduction in accidents.
The further process done is the shape identification. In this the shape of the image will be studied. There are very large number of traffic symbols present and they are classified according to their shape, size and the message it reveals. Once the shape is identified it is compared with the images already stored in the database. Here the Pearson co-relation plays a vital role and hence it is mandatory to perform this task. It gives us the ratio image which matches the images stored in the database. Later by undergoing all these procedures the captured image is finally recognized. We can say that the user have achieved the goal of identifying the captured image. The traffic sign
In this paper the system will take the images of traffic signs as input, do the required processing and the output will be based on the required voice alerts. The building blocks the system are explained further. Almost a very large range of traffic symbols are © 2017, IRJET
|
Impact Factor value: 5.181
|
ISO 9001:2008 Certified Journal
|
Page 797