Main Article Content

K. Prathyusha


Millions of people are injured annually in vehicle accidents. Most traffic accidents are the result of carelessness, ignorance of the rules, and neglect of traffic signboards, both at the individual level by the drivers and the society at large. The magnitude of road accidents in India is alarming. This is evident from the fact that every hour there are about 56 accidents taking place similarly, every hour more than 14 deaths occur due to road accidents. When someone neglects to obey traffic signs, they are putting themselves at risk as well as other drivers, their passengers, and pedestrians. All the signs and signals help keep order in traffic and they also are designed to reduce the number and severity of traffic accidents. Some drivers believe that some traffic signs are simply not necessary.


Download data is not yet available.


Metrics Loading ...

Article Details

How to Cite
VALLABHAPURAPU, N. J., S. . SURA, P. CHERIPALLY, K. KONAMGERI, and K. Prathyusha. “The TRAFFIC SIGN BOARD RECOGNITION AND VOICE ALERT SYSTEM”. Technix International Journal for Engineering Research, vol. 9, no. 6, June 2022, pp. 128-32,
Research Articles


Bangquan X, Xiong WX (2019)Real-time Huo A, Zhang W, Li Y (2020) Traffic sign recognition based on improved SSD model. International Conference on Computer Network, Electronic and Automation

Jin Y, Fu Y, Wang W, Guo J, Ren C, Xiang X (2020)Multi-feature fusion and enhancement single shot detector for traffic sign recognition. IEEE Access 8:38931–38940

Kuznetsova A, Maleva T, Soloviev V (2020) Detecting apples in orchards using YOLOv3 and YOLOv5 in general and close-up images. International Symposium on Neural Networks

Li S, Gu X, Xu X, Xu D, Zhang T, Liu Z, Dong Q (2021) Detection of concealed cracks from ground penetrating radar images based on deep learning algorithm. Constr Build Mater 273:121949

Lian J, Yin Y, Li L, Wang Z, Zhou Y (2021) Small object detection in traffic scenes based on attention feature fusion. Sensors 21(9):3031

Lim K, Hong Y, Choi Y, Byun H (2017)Real-time traffic sign recognition based on a general purpose GPU and deep-learning. PLoS One 12(3):e0173317

Liu X, Yan W (2021)Traffic-light sign recognition using capsule network. Multimed Tools Appl 80:15161–15171

embedded traffic sign recognition using efficient convolutional neural network. IEEE Access 7:53330–53346

Chen Q, Huang N, Zhou J, Tan Z (2018) An SSD algorithm based on vehicle counting method. Chinese Control Conference

Ellahyani A, Ansari M, Lahmyed R, Trémeau A (2018) Traffic sign recognition method for intelligent vehicles. J Opt Soc Am35(11):1907–1914.

Garg P, Chowdhury DR, More VN (2019) Traffic sign recognition and classification using YOLOv2, Faster R-CNN and SSD. International Conference on Computing, Communication and Networking Technologies

Hao G, Yingkun Y, Yi Q (2019) General target detection method based on improved SSD. IEEE Joint International Information Technology and Artificial Intelligence Conference

He Z, Nan F, Li X, Lee SJ, Yang Y (2020) Traffic sign recognition by combining global and local features based on semi-supervised classification. IET Intel Transport Syst 14(5):323–330

Hinton GE, Salakhutdinov RR (2006) Reducing the dimensionality of data with neural networks. Science 313(5786):504–507

Hu GX, Hu BL, Yang Z, Huang L, Li P (2021) Pavement crack detection method based on deep learning models. Wirel Commun Mob Comput 2021.

Similar Articles

You may also start an advanced similarity search for this article.