Phase Transform for Object and Shape Detection in Digital Images

Abstract

Object and shape detection in digital images utilizing edge detection is described. In a first edge detection approach, phase transformation is utilized in the frequency domain, such as in response to Fourier transform, followed by use of a frequency-domain phase kernel and inverse-Fourier transform. Edge detection is also provided using a phase transform in the spatial domain utilizing a convolution approach. In a second edge detection approach, phase stretching is utilized, such as in combination with phase histogramming along with thresholding and morphological operations. Numerous example images are provided illustrating benefits of the disclosed technology with different applications and under different conditions.

What is claimed is: 
     
         1 . A method of performing edge detection on a digital image, comprising:
 receiving a digital image within an image processing device;   applying a nonlinear frequency dependent phase operation to the digital image;   applying a phase kernel during said phase operation so that total amount of phase applied in said phase kernel determines sharpness of image edges being extracted from the digital image;   wherein edge detection is based on phase within a complex image after application of the phase kernel from said nonlinear frequency dependent phase operation; and   generating an image output as a phase image output with phase of the transformed image as output.