A Method of Image Edge Detection Based on Fourier Transform

Abstract

The invention discloses an image edge detecting method based on Fourier transformation. The method comprises the following steps: step 100, a black and white digital image I is obtained; step 200, Gaussian filtering is conducted to the image I, and then a filtered image Is is obtained; step 300, Fourier transformation is conducted to the image Is, and then frequency spectrum Fs of the Is is obtained; step 400, each frequency spectrum component Fs (km, kn) is multiplied by a phase shift factor so as to obtain a new frequency spectrum component, wherein km=0, 1, ..., M-1, and kn=0, 1, ..., N-1, the km and the kn are respectively wave numbers in the X direction and the Y direction, and x0 and y0 are respectively the offset amount in the X direction and the Y direction; step 500, an offset image Ib (m, n) is obtained after Fourier inversion transformation, wherein m=1, 2, ..., M, and n=1, 2, ..., N, and M and N are pixel numbers in the X direction and the Y direction; and step 600, the offset image Ib minus an original image I pixel-by-pixel, an absolute value Ie (m, n)=| Ib (m, n)-I (m, n) | is obtained, and the Ie is an obtained edge feature image. The method has the advantages of being high in calculating precision, fast in calculating speed and good in noise inhibiting ability.

Description

technical field [0001] The invention relates to the field of image and video data processing, in particular to an image edge detection method based on Fourier transform. Background technique [0002] Edge detection is a basic problem in image processing and computer vision. The purpose of edge detection is to identify points in digital images with obvious brightness changes. Significant changes in image attributes usually reflect important events and changes in attributes. These include: 1. Discontinuities in depth, 2. Discontinuities in surface orientation, 3. Changes in material properties, 4. Changes in scene lighting. Edge detection is a research field in image processing and computer vision, especially in feature extraction. [0003] Image edge detection greatly reduces the amount of data, and eliminates information that can be considered irrelevant, while retaining important structural properties of the image. There are many methods for edge detection, and most of t...

AI Technical Summary

Problems solved by technology

1. The accuracy is not high

Since only a small amount of local information is used, this information cannot accurately describe the edge change characteristics of the object, so the calculation accuracy is limited

2. Sensitivity to noise

When there is relatively strong noise, it is basically impossible to detect edges of various scales

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