Graph spectral domain feature representation for in-air drawn number recognition

The emerging field of graph signal processing has brought new scope in understanding the spectral properties of arbitrary structures. This paper proposes a novel graph spectral domain feature representation scheme for recognising in-air drawn numbers. It provides the solution by forming the hand's path as a graph and extracting its features based on the spectral domain representation by computing the graph spectral transform. A novel graph generation model is proposed to form the topology of the shapes of numbers. The experiments show that the proposed features are flip and rotation-invariant which makes insensitive to changes in the rotation angle of the drawn numbers. The proposed solution achieves a high level of accuracy of nearly 98% for in-air hand drawn number recognition.