NAVIGATR: DETECTING AND RECOGNIZING TURKISH TRAFFIC SIGNS USING A NEW DATASET BASED ON DEEP LEARNING

Year 2023, Volume: 1 Issue: 1, 44 - 53, 02.02.2024

Erdi Tuna Kasım Özacar

Abstract

While cars are becoming smarter than ever with built-in sensing technologies, thanks to the spreading availability of low-cost wearable devices, millions of cars in traffic lack such technologies. However, detecting and recognizing traffic signs is essential in ensuring the safety of pedestrians and drivers. To provide this safety, we conducted a study first to prepare a dataset using collected data in different weather conditions. Then, we used TensorFlow’s Object Detection API to detect and recognize traffic signs in Turkey. Initially, we collected over 5000 pieces of data for training. We labeled the data in the dataset using a web-based helper application and selected a suitable deep-learning model. After the training process, we evaluated the results of the models and assessed the quality of our prepared dataset. After training the model, we imported it into an Android application that we developed. This application helps navigate drivers by providing information about the signs in front of their cars using text-to-speech technology.

Keywords

TensorFlow Object Detection API, TTSD, traffic sign detection.

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