Vehicle Type Image Dataset (Version 1): VTID1

Published: 24 November 2021| Version 1 | DOI: 10.17632/r7bthvstxw.1


The main objective for the use of an image dataset was to examine the five vehicle types of motor vehicles that were the most commonly used ones in Thailand (sedan, hatchback, pick-up, SUV, and van). The recording devices to collect the images were part of a video surveillance system located at Loei Rajabhat University in Loei province, Thailand. The collection process took place during the daytime for four weeks between July and December 2018. Two cameras were installed at the front gate of the university. However, a small number of van images was produced in the dataset compared to the number of images of the other four vehicle types. Because of this, the researchers decided to add other vehicle-type images such as those of motorcycles into the van group and changed the name of the group to "other vehicles" to increase diversity. Finally, the first dataset called "Vehicle Type Image Dataset (VTID)" had a total of 1,410 images that could be separated into vehicle types as follows; 400 sedans, 478 pick-ups, 129 SUVs, 181 hatchbacks, and 122 other vehicle images. Each image was collected using the 224x224 pixel resolution.



Image Classification, Convolutional Neural Network