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Method and system for extracting field image edges of plant leaves

A technology for image edges and plant leaves, applied in image enhancement, image data processing, instruments, etc., to achieve the effects of good noise suppression, fast computing speed, and wide application range

Active Publication Date: 2013-03-06
CHINA AGRI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is to improve the accuracy and completeness of field image edge extraction for plant leaves with uneven gray levels

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  • Method and system for extracting field image edges of plant leaves
  • Method and system for extracting field image edges of plant leaves
  • Method and system for extracting field image edges of plant leaves

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Embodiment Construction

[0055] The method and system for extracting the edge of a plant leaf field image proposed by the present invention are described in detail below in conjunction with the accompanying drawings and embodiments.

[0056] The method and system of the present invention aim at the situation that the gray level of the plant leaf image on the site is not uniform and it is difficult to accurately extract the complete leaf by simply using the graphic image algorithm.

[0057] The method and system of the present invention take the sub-region containing a single leaf as the target image, and take the segmented region sub-image locked near the sub-region as the processing object; comprehensively utilize graphic image processing operators to enhance and denoise the regional sub-image ;Aiming at the uneven gray level of leaves on the plant site, use morphological processing to homogenize the gray level; then use the method of threshold and Canny operator segmentation to extract the edge of th...

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Abstract

The invention relates to a method and a system for extracting field image edges of plant leaves. The method comprises the following steps of: 1, smoothing and denoising a subimage in a partition area adjacent to an area containing a single leaf serving as a target image; 2, performing area-based threshold partition and gradient-based edge detection partition on the image processed by the step 1, and performing initial optimization to acquire an inner template of a target area; 3, judging whether the target area of the image processed by the step 2 is a leaf image or not, if so, executing the step 4, and otherwise, performing grayscale mapping and morphological reconstruction on the image processed by the step 1, and executing the step 2; and 4, performing operation of adhesion disconnection, false edge removal and closure on the image processed by the step 2 to obtain the edge image with a closed edge. The method and the system improve the accuracy and integrality of the extraction of the field image edges, which have non-uniform grayscale, of the plant leaves.

Description

technical field [0001] The invention relates to the technical field of digital image processing, in particular to a method and system for extracting edges of field images of plant leaves. Background technique [0002] Digital image processing technology is an interdisciplinary field. With the continuous development of computer science and technology, image processing and analysis has gradually formed its own scientific system, and new processing methods emerge in endlessly. Although its development history is not long, it has attracted widespread attention from all walks of life. First of all, vision is the most important means of human perception, and images are the basis of vision. Therefore, digital images have become an effective tool for scholars in many fields such as psychology, physiology, and computer science to study visual perception. Second, image processing has a growing demand in large-scale applications such as military, remote sensing, and meteorology. [0...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
Inventor 王建仑董金勇何建磊李道亮王永彬欧阳常奇
Owner CHINA AGRI UNIV
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