Krawtchouk Moments for Gait Phase Detection

Abstract

We present a novel method for gait phase detection based on Krawtchouk moments, which can be used in gait analysis. The low computational cost and high capacity of description of the Krauchouk moments makes it easy detect the parameters of the gait cycle, such as the swing phase, stance phase and double support. In addition, we present the results of the gait phases detection with the proposed method of 10 test subjects and compared with standard values.

Stable Calculation of Krawtchouk Functions from Triplet Relations

“…In the digital age, the discrete polynomials are especially popular and those with a finite support (discrete Chebyshev and Krawtchouk) have been used in various signal processing tasks, but dominantly for image processing. Examples of applications of Krawtchouk polynomials can be found in, e.g., [1][2][3][4][5][6][7].…”

Reconstruction of color biomedical images by means of quaternion generic Jacobi-Fourier moments in the framework of polar pixels

“…In recent years, moments have been successfully used in a variety of research areas such as image registration, 1 face recognition, 2 angle estimation, 3 watermarking, 4 pattern reconstruction, 5 medical imaging, [6][7][8] focus measures, 9 image analysis, 10 forensic applications, 11 gait phase detection, 12 and so forth. In the 1960s, Hu 13 introduced a set of invariants based on the low-order geometric moments for pattern recognition tasks.…”