Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Scallop shell growing pattern segmentation and recognition method

A recognition method and technology for shells, applied in character and pattern recognition, image analysis, image data processing, etc., can solve the problems of measurement errors and inaccurate manual readings, and achieve high accuracy, simple and rapid measurement and calculation, and throughput. big effect

Active Publication Date: 2017-03-22
OCEAN UNIV OF CHINA
View PDF6 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

These studies only stop at the function fitting of shell data measured regularly during the growth process of scallops, which requires long-term follow-up measurements of scallops, and is also limited by measurement errors and inaccurate manual readings

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
  • Scallop shell growing pattern segmentation and recognition method
  • Scallop shell growing pattern segmentation and recognition method
  • Scallop shell growing pattern segmentation and recognition method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0054] 1. Shell material and CT image acquisition.

[0055] The 24-month-old Ezo scallop (shell height 125.28±2.85 mm) was taken from Zhangzidao Sea Area, Changhai County, Dalian City in January 2013. After removing the soft parts, the inner and outer surfaces of the shell were washed three times with triple distilled water. Images were acquired using a digital medical diagnostic X-ray fluoroscopy system (Uni-Vision).

[0056] 2. Use the two-dimensional Gaussian kernel matching filter to enhance the features of the shell texture.

[0057] The two-dimensional Gaussian function has rotational symmetry, that is, the smoothness of the filter is the same in all directions. In the scallop CT image obtained in step 1, the curvature of the tubular lines is small and the change of the tube width is gradual (see figure 2 a), the cross-sectional gray profile of the tubular grain can be approximated by a Gaussian-type curve (see figure 2 b) Therefore, the shell pattern is defined as ...

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 provides a scallop shell growing pattern segmentation and recognition method. After a scallop shell CT image is acquired, Gaussian kernel matching filter is used to enhance the tubular pattern matching. The enhanced image is iterated. Each time of iteration retains the pattern characteristic information, and acquired fine patterns are segmented. According to the invention, the comb shell CT image is used as an input image; Gaussian kernel matching filter is used to enhance the tubular pattern matching in the image; the image segmentation of full variational model image binarization is carried out; intersections in an image pattern network are recognized; the information of a large number of scallop growing points is acquired; and the premise of the scallop growth rate is further accurately calculated. Compared with a traditional time measurement method, the method has the advantages that simple and rapid measurement and calculation are realized through computer analysis; and the method has the advantages of high accuracy and large flux; and the method provides a basis for acquiring accurate breeding phenotype information for shellfish breeding in the future.

Description

technical field [0001] The invention belongs to the technical field of shellfish genetics and breeding, and in particular relates to a method for segmenting and identifying scallop shell growth lines. Background technique [0002] Shells are calcifications secreted by the mantle of shellfish to protect the soft body. Due to the influence of their own and seasonal environmental changes, shellfish will form growth lines in the process of secreting calcification to form shells. The texture appears as different fine grooves on the surface, different densities on the internal structure, and changes in elements on the composition. Studying shell patterns can not only obtain objective and rapid growth information (growth traits) of scallops, but also accurately reveal the specific growth process of shellfish life history, and more importantly, provide basic data for shellfish breeding. [0003] Patinopectenyessoensis is native to the southern part of the Kuril Islands in Russia, ...

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): G06K9/46G06K9/34G06T5/00
CPCG06T5/00G06T2207/10081G06V10/267G06V10/44
Inventor 邢强王扬帆魏腾达李玉强张玲玲王师胡晓丽陆维包振民
Owner OCEAN UNIV OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com