Static gestures of Indian Sign Language (ISL) for English Alphabet, Hindi Vowels and Numerals

Published: 24 August 2022| Version 1 | DOI: 10.17632/7tsw22y96w.1
Animesh Singh,


This dataset consists of static hand gestures and lips movement for each character in the English alphabet, eight Hindi Vowels and ten Numerals as represented in Indian sign language (ISL). The dataset consists of 1,02,470 images of subjects from different age groups presenting static gestures under varied backgrounds and illumination conditions. The dataset is structured into three folders namely Kids, Teenagers and Adults. Each folder consists of sub-folders namely Full Sleeves and Half Sleeves indicating the type of clothing that the subject has worn at the time of image acquisition. In each sub-folders, images for the English alphabet, Hindi Vowels and Numerals are stored respectively in the sub-folders named with that specific character. However, for the English alphabet 'E' and Numeral '9' we have captured two different signs for each (that are used interchangeably), and it is contained in the folder namely E1 and E2 for alphabet 'E' and 9a and 9b for Numeral '9'. For the English alphabet, wherever a character is represented by a dynamic sign, the last frame of the sign is captured. For example, this is typically a case with English characters like 'J', 'H' and 'Y'. The images are stored in .jpeg format and have resolutions varying from 300 x 500 to 800 x 600, and the size is less than 100KB. The dataset is captured by a team pursuing research at Chandigarh College of Engineering and Technology, Chandigarh. The subjects have been informed about the research and Informed Participant Consent has been obtained prior to image acquisition. This dataset can be used only for research purposes either as it is or after cropping the static gestures from the image after duly referencing it. Any other use of the dataset is strictly prohibited and any illegal use is subject to the Indian court of law.


Steps to reproduce

This dataset is captured using a smartphone camera. The subjects are present in varying backgrounds and under different illumination conditions. The resolution of the cameras used for this purpose is at least 8MP. The images are acquired from an approximate distance of 3 feet from the subject so that the upper half of the body is visible in the captured image. This dataset consists of static hand gestures of the Indian sign language along with the lips movement for each character in the English alphabet, eight Hindi Vowels and ten Numerals. The researchers can use the dataset by cropping the hand gestures or can use it in a multimodal approach that consists of both hand gestures and lips movement for Indian sign language recognition. This dataset is unique in itself as the captured images are from different age groups like Kids, Teenagers and Adults. The inclusion of subjects from different age groups gives variety in hand shape and size. This dataset consists of more than one lakh images of static gestures for Indian sign language. A minimum of 2000 images (approx.) for each character is taken. The number of subjects involved in the creation of the dataset are four Kids, twenty-three Teenagers and six Adults out of which seventeen are Females and sixteen are Males.


Panjab University, Chandigarh College of Engineering and Technology, University Institute of Engineering and Technology


Computer Vision, Machine Learning, Machine Learning Algorithm, Gesture Analysis, Sign Language, Gesture, Deep Learning, Computer Vision Algorithms, Gesture Recognition