BdSL47: A Complete Depth-based Bangla Sign Alphabet and Digit Dataset

The BdSL47 is the original dataset constructed under the supervision of the Systems and Software Lab (SSL), Department of Computer Science and Engineering (CSE), Islamic University of Technology (IUT) and Department of Computer Science and Engineering (CSE), United International University (UIU), Dhaka, Bangladesh. The ownership of this dataset belongs to the authors and they have administered the dataset collection processes by taking informed consent from the participants/singers of the Bangla sign Alphabets and Digits. The dataset was constructed by collecting Bangla alphabet signs from 10 signers in a controlled setting. We employed varying factors of the users like age, gender, hand shape, and skin color. We have also incorporated different challenges while collecting data like scaling, translation, hand rotation, hand orientation, lighting ambiance, and background. We have collected webcam images of 47 signs (10 Bangla Sign Digits and 37 Bangla Sign Alphabet) and resized them to 640x480. For each of the RGB image samples, we have detected the hand key points via the MediaPipe library. Then we generate CSV files containing x, y, and depth coordinate values of 21 hand key points extracted from these image samples and constitute 21×3, or 63 input features. The dataset contains 47000 RGB input images of 47 signs (10 digits, 37 letters) of Bangla Sign Language. The images have been processed via the MediaPipe framework, which is designed to detect predefined 21 hand key points from a sample and provide normalized x & y coordinate values and an estimated depth value. The 3D coordinate values were stored in .csv files (1 file contains information on 100 image samples of the same sign). The dataset contains 470 .csv files in total. There are two folders named as “Bangla Sign Language Dataset - Sign Alphabets” and “Bangla Sign Language Dataset - Sign Digits”. Under each folder, user-wise folders are given that contain sign images (input images (raw images in jpg format), and CSV files (normalized 3D coordinates of 21 hand keypoints with corresponding class labels). All the files of around 1.12GB are available for direct download using the ‘Download All’ option by going to the doi: 10.17632/pbb3w3f92y.3. The images and CSV files can be easily read or processed using Python or any other programming language (Python 3.10.3). Please cite our dataset if you have used it in your research following the format, “Rayeed, S M; Tuba, Sidratul Tamzida; Mahmud, Hasan; Mazumder, Mumtahin Habib Ullah; Hossain, Md. Saddam; Hasan, Md. Kamrul (2023), “BdSL47: A Complete Depth-based Bangla Sign Alphabet and Digit Dataset”, Mendeley Data, V3, doi: 10.17632/pbb3w3f92y.3”. The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International license. The link to the code can be found here: https://github.com/SMRayeed/BdSL47-Recognition.

BdSL47是由孟加拉国达卡的伊斯兰科技大学（Islamic University of Technology, IUT）计算机科学与工程系（Department of Computer Science and Engineering, CSE）系统与软件实验室（Systems and Software Lab, SSL）以及联合国际大学（United International University, UIU）计算机科学与工程系（CSE）联合指导构建的原始数据集。

本数据集的所有权归作者所有，作者通过获得孟加拉语手语字母与数字参与者/手语者的知情同意，完成了数据集的全部采集流程。

该数据集通过在受控环境下从10名手语者处采集孟加拉语手语手势构建。我们纳入了用户的多维度属性，包括年龄、性别、手型与肤色；同时在数据采集过程中设置了多种挑战场景，涵盖缩放、平移、手部旋转、手部朝向、光照环境与背景变化。

我们采集了47种手语手势的网络摄像头图像（含10个孟加拉语手语数字与37个孟加拉语手语字母），并将所有图像统一调整至640×480分辨率。针对每张RGB图像样本，我们通过MediaPipe库检测手部关键点。随后生成包含21个手部关键点的x、y与深度坐标值的逗号分隔值（Comma-Separated Values, CSV）文件，由此构建出21×3（即63个）输入特征。

本数据集包含47种手语手势（10个数字、37个字母）的47000张RGB输入图像。这些图像已通过MediaPipe框架处理——该框架可从样本中检测预设的21个手部关键点，并输出归一化的x、y坐标值与估算的深度值。三维坐标值存储于CSV文件中（单个CSV文件包含同一种手势的100张图像样本的信息）。本数据集总计包含470个CSV文件。

数据集设有两个文件夹，分别命名为"Bangla Sign Language Dataset - Sign Alphabets"（孟加拉语手语数据集-手语字母）与"Bangla Sign Language Dataset - Sign Digits"（孟加拉语手语数据集-手语数字）。每个文件夹下均设有按使用者划分的子文件夹，其中包含手语图像（jpg格式的原始输入图像）与CSV文件（含21个手部关键点的归一化三维坐标及对应类别标签）。

本数据集全部约1.12GB的文件可通过访问DOI: 10.17632/pbb3w3f92y.3，使用"全部下载"选项直接获取。图像与CSV文件可通过Python或其他编程语言（如Python 3.10.3）轻松读取与处理。

若您在研究中使用本数据集，请按照以下格式引用："Rayeed, S M; Tuba, Sidratul Tamzida; Mahmud, Hasan; Mazumder, Mumtahin Habib Ullah; Hossain, Md. Saddam; Hasan, Md. Kamrul (2023), "BdSL47: A Complete Depth-based Bangla Sign Alphabet and Digit Dataset", Mendeley Data, V3, doi: 10.17632/pbb3w3f92y.3"。

本数据集相关文件采用知识共享署名4.0国际许可协议进行授权。代码链接可访问：https://github.com/SMRayeed/BdSL47-Recognition。

搜集汇总

背景与挑战

背景概述

BdSL47是一个基于深度的孟加拉手语字母和数字数据集，包含47个符号（10个数字和37个字母），由10名手语者在受控环境中收集，并考虑了多种用户因素和挑战。数据集提供47,000张RGB图像及其处理后的21个手部关键点3D坐标（存储为CSV文件），总大小约1.12GB，适用于手语识别研究。