Page 158 - 2024-Vol20-Issue2

Received: 23 July 2023 | Revised: 24 September 2023 | Accepted: 5 November 2023

DOI: 10.37917/ijeee.20.2.13 Vol. 20 | Issue 2 | December 2024

Open Access

Iraqi Journal for Electrical and Electronic Engineering

Review Article

Advancements and Challenges in Hand Gesture

Recognition: A Comprehensive Review

Bothina Kareem Murad1, Abbas H. Hassin Alasadi *1,2
1College of Computer Science and Information Technology, University of Basrah, Basrah, Iraq.
2IEEE and ACIT member, Tel: 009647809835559, ORCID: (0000-0002-6627-4456) (orcid.org)

Correspondance
* Abbas H. Hassin Alasadi
College of Computer Science and Information Technology,
University of Basrah, Basrah, Iraq.
Email: abbas.hassin@uobasrah.edu.iq or abbashh2002@gmail.com

Abstract
Hand gesture recognition is a quickly developing field with many uses in human-computer interaction, sign language
recognition, virtual reality, gaming, and robotics. This paper reviews different ways to model hands, such as vision-based,
sensor-based, and data glove-based techniques. It emphasizes the importance of accurate hand modeling and feature
extraction for capturing and analyzing gestures. Key features like motion, depth, color, shape, and pixel values and their
relevance in gesture recognition are discussed. Challenges faced in hand gesture recognition include lighting variations,
complex backgrounds, noise, and real-time performance. Machine learning algorithms are used to classify and recognize
gestures based on extracted features. The paper emphasizes the need for further research and advancements to improve
hand gesture recognition systems’ robustness, accuracy, and usability. This review offers valuable insights into the
current state of hand gesture recognition, its applications, and its potential to revolutionize human-computer interaction
and enable natural and intuitive interactions between humans and machines. In simpler terms, hand gesture recognition
is a way for computers to understand what people are saying with their hands. It has many potential applications, such
as allowing people to control computers without touching them or helping people with disabilities communicate. The
paper reviews different ways to develop hand gesture recognition systems and discusses the challenges and opportunities
in this area.

Keywords
Hand gesture recognition, HCI, Sign language recognition, Feature extraction, Machine learning algorithms.

I. INTRODUCTION the foundation of language and can convey various types of
information. Without gestures, actions and movements are
Human gesture recognition is a challenging and significant incomplete, lacking genuine feelings and thoughts. Pointing
field in computer science, aiming to interpret human gestures finger gestures can indicate time and space, indicating needs
using mathematical models. or wishes among people.
Gestures are nonverbal communication methods using the Hand gestures can be categorized into conversational, control-
body’s movement to convey messages, originating from var- ling, manipulated, and communication [2, 3]. Sign language
ious parts of the human body, with the most common ones is a crucial state of communication gestures used in vision al-
coming from the hand or face. In Webster’s dictionary [1], it gorithms for structural analysis. Analyzing pointing gestures
can find: for virtual identification is essential in Vision-Based Interface
”A gesture is a movement usually of the body or limbs that (VBI) research. Navigating gestures capture hand direction
expresses or emphasizes an idea, sentiment, or attitude.” Ges- as 3D directional, while manipulated gestures enable natural
tures are essential for human communication, as they are

This is an open-access article under the terms of the Creative Commons Attribution License,
which permits use, distribution, and reproduction in any medium, provided the original work is properly cited.
©2023 The Authors.
Published by Iraqi Journal for Electrical and Electronic Engineering | College of Engineering, University of Basrah.

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