Watershed texture imaging segmenting method based on morphology Haar small wave texture gradient extraction

A texture gradient and texture image technology, applied in the field of image processing, can solve problems such as watershed over-segmentation

Active Publication Date: 2009-07-29
XIDIAN UNIV
View PDF0 Cites 23 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a texture segmentation image algorithm based on morphological Haar wavelet and watershed, which solves the over-segmentation p

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Watershed texture imaging segmenting method based on morphology Haar small wave texture gradient extraction
  • Watershed texture imaging segmenting method based on morphology Haar small wave texture gradient extraction
  • Watershed texture imaging segmenting method based on morphology Haar small wave texture gradient extraction

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0057] Preferred embodiments of the present invention will be described in detail with reference to the above-mentioned drawings.

[0058] Such as image 3 As shown, the present invention carries out the method for image segmentation comprising the following steps:

[0059] 1. Perform morphological Haar wavelet transform on the original image to obtain its high-frequency sub-band diagrams in three directions: horizontal, vertical, and diagonal.

[0060] On the basis of the one-dimensional form Haar wavelet, the present invention can obtain the two-dimensional form Haar wavelet by using the method of separating filter groups (such as sequentially applying the one-dimensional form Haar wavelet transform to the row and column of the two-dimensional image). The two-dimensional form Haar wavelet decomposition of the image will get a low-frequency component and three high-frequency components, namely the horizontal component, vertical component and diagonal component. Such as fi...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a segmentation method of a watershed texture image on the basis of morphological Haar wavelet gradient extraction, which relates to the technical filed of image processing and aims at solving the excessive segmentation problem of watershed texture image segmentation. The method not only can reduce excessive segmentation, but also is much better than other post processing methods solving the problem of excessive segmentation in arithmetic speed. The steps for realizing the method are as follows: (1) a texture gradient image TG is extracted by carrying out morphological Haar wavelet conversion to the original texture image; (2) after circumrotating by 90 degrees, the original image is used for extracting a texture gradient image RTG with a morphological Haar wavelet; (3) the texture gradient image RTG and the texture gradient image TG are subjected to circumrotation weighting to obtain a texture gradient image G; (4) morphological filtering is carried out to the texture gradient image G to obtain a texture gradient image OCG after being smoothed; and (5) marker-watershed segmentation is carried out to the texture gradient image OCG to obtain the final texture segmentation result. Compared with the image segmentation standards, the image segmentation result of the method is validated to basically meet standards.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to an application in the field of texture image segmentation, in particular to a watershed texture image segmentation method based on morphological Haar wavelet texture gradient extraction. Background technique [0002] Image segmentation is a very important step in image processing, which divides an image into subregions or objects with strong correlations. Image segmentation is usually used for further image analysis, recognition, compression coding, etc. The accuracy of segmentation directly affects the effectiveness of subsequent tasks, so it is of great significance and is a very important step in image processing. Image segmentation algorithms generally fall into the following categories: threshold-based segmentation, edge-based segmentation, and region-based segmentation. The advantage of threshold-based segmentation is that the algorithm is simple, and closed and con...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06T5/00G06T7/00
Inventor 焦李成张晓静王爽侯彪刘芳公茂果梁建华
Owner XIDIAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products