Tea image enhancement and division method based on color characteristic

A technology of image enhancement and color features, applied in the field of image processing, can solve problems such as rough segmentation, under-segmentation, and poor performance, and achieve good experimental results and good visual effects

Inactive Publication Date: 2012-10-17
SICHUAN AGRI UNIV +1
View PDF1 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

There are many existing color image segmentation methods. The commonly used threshold method requires obvious peaks and valleys in the histogram, which tends to cause rough segmentation and poor performance in the processing of color images; and the feature space segmentation method combines image domain Local information and spatial information, local decision-making is strong against noise interference, but it is easy to cause under-segmentation

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
  • Tea image enhancement and division method based on color characteristic
  • Tea image enhancement and division method based on color characteristic
  • Tea image enhancement and division method based on color characteristic

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0051] The digital camera used in the experiment is CANON S80. In the process of image acquisition, close-range mode is adopted, and the flashlight is turned off to avoid the influence of the light of the flashlight on the tea color. At the same time, the image should be taken under natural light and avoid direct sunlight. The focal length of the image taken in the image is 25cm, and the resolution is 1600×1200.

[0052] Experiments have found that when the focal length of the image is closer, the number of tea buds obtained is less, and the accuracy of segmentation is higher, and the accuracy of segmentation is the highest when there are 4-8 buds. When the focal length is closer, it will affect the depth of field and the clarity of imaging, thereby affecting the accuracy of segmentation, but when the focal length is the farthest, the imaging image of shoots will be reduced, the range of image color will be wider, and the accuracy of segmentation will also be improved. decline...

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 relates to the field of an imaging processing technology and discloses a tea image enhancement and division method based on a color characteristic. The tea image enhancement and division method comprises the following steps of: firstly, converting an original tea RGB (Red, Green and Blue) colored image into an HIS (Hue, Intensity and Saturation) color space; carrying out convergence calculation based on a characteristic hue on a hue H and carrying out adjustment and calculation based on an expected value on a saturation S; then, carrying out primary seed selection on hue and saturation parameters, and then carrying out regional growth on the seed region based on the similarity of colors and the connective characteristics of the region; combining a color distance and an edge distance to carry out the growth and the combination of the region; and finally, finishing the division of tea tender shoots. With the adoption of conversion, enhancement and division tests of a tea image color space, a result shows that the algorithm can better keep the color characteristic and can better divide the tea tender shoots from a tea image, so that a new method is provided for growth monitoring and nondestructive testing for teas.

Description

Technical field [0001] The present invention is a method of image processing technology. It is a method of enhancement of tea images based on color characteristics of tea images and tender tender buds based on regional growth. Background technique [0002] Image processing technology is developed rapidly in recent years with the development and maturity of computers -an important application technology field. In the production of modern fine agriculture, the use of computer image technology can greatly improve accuracy and efficiency, realize information collection andThe processing of processing and intelligence can be monitored without damage, fast, and real -time monitoring of the growth of cash crops.There have been some research on the analysis and identification of the color and quality of the computer technology, but the previous research is mostly researching the shape and color of the finished tea leaves or the soup color of the tea.There are few corresponding studies at...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T7/00
Inventor 汪建杜世平曾宪垠王开明
Owner SICHUAN AGRI 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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap