Robust hand gesture recognition system based on a new set of quaternion Tchebichef moment invariants

Abstract

Hand gesture recognition is a challenging task due to the complexity of hand movements and to the variety among the same gesture performed by distinct subjects. Recent technologies, such as Kinect sensor, provide new opportunities, allowing to capture both RGB and depth (RGB-D) images, which offer high discriminant information for efficient hand gesture recognition. In the aspect of feature extraction, the traditional methods process the RGB and depth information independently. In this paper, we propose a robust hand gesture recognition system based on a new feature extraction method, fusing RGB images and depth information simultaneously, by using the quaternion algebra that provide a more robust and holistical representation. In fact, we introduce, for the first time, a novel type of feature extraction method, named quaternion Tchebichef moment invariants. The novelty of the proposed method in this paper lies in the direct derivation of invariants from their orthogonal moments, based on the algebraic properties of the discrete Tchebichef polynomials. The proposed approach based on quaternion algebra is suggested to process the four components holistically, for a robust and efficient hand gesture recognition system. The obtained experimental and theoretical results demonstrate that the present approach is very effective for addressing the problem of hand gesture recognition and have proved its robustness against geometrical distortion, noisy conditions and complex background compared to the state of the art, indicating that it could be highly useful for many computer vision applications. Keywords Hand gesture recognition • Tchebichef moments • Moment invariants • Quaternion algebra • Complex background • RST invariants

Static hand gesture recognition based on hierarchical decision and classification of finger features

“…Both the feature vector and the neural network were tuned by a multi-objective evolutionary algorithm. Elouariachi et al 24 proposed a quaternion Tchebichef moment invariants by using the quaternion algebra for extracting the gesture features. Based on the algebraic properties of the discrete Tchebichef polynomials, the direct derivation of invariants from their orthogonal moments has the robustness against geometrical distortion, noisy conditions and complex background.…”

Recognition and Classification of Dynamic Hand Gestures by a Wearable Data-Glove

“…The majority of works concerning gesture and SL recognition uses cameras or other external devices for data acquisition (e.g. [2,3,9,10,12,18,20,22,23,[38][39][40][41]). The main advantage of this solution is the acquisition of all data required for a perfect SL translation, such as position, configuration and movement of the hands, facial expressions, position and movement of the body.…”