Rapid Extraction of Clothing Sample Profile Based on the Improved Canny Algorithm
Na Liu, Yanyan Ma, Linyi Shao and 1 more
Advances in Multimedia · 2022
doi:10.1155/2022/7554652 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
In order to reduce the difficulty of clothing diversity on the edge extraction link, this study proposes an improved Canny algorithm that segments the pattern, styles, and contours of the clothing image after creating a sample library of a women’s image. Extract, improve the accuracy of the edge, and reduce the noise formed by texture and clothing. The results show that in the simulation experiment, the contour extraction of multiple categories of clothing is carried out, and compared with the differential operator algorithm and Canny algorithm, the experimental results show that the improved algorithm can more accurately segment the edge of clothing, extract the style contour, and express the characteristics of clothing.
Abstract licence: CC BY
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.