Fruit shape detection by optimizing Chan-Vese model

Zhouxiang Shou; Qihui Wang; Jiangsheng Gui; Yuhuai Wang

doi:10.1117/12.832308

30 October 2009 Fruit shape detection by optimizing Chan-Vese model

Zhouxiang Shou, Qihui Wang, Jiangsheng Gui, Yuhuai Wang

Proceedings Volume 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis; 74950W (2009) https://doi.org/10.1117/12.832308
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Applications of machine vision for automated inspection and sorting of fruits have been widely studied by scientists and engineers. In these applications, edge detection, segmentation, and shape recovery are difficult problem. Previous studies have usually adopted some preprocessing such as noise removal and motion deblurring before using a threshold method to detect shape boundary. In many cases, however, this manner is troubled and not unified and does not work well. This research proposes a novel approach for fruit shape detection in RGB spaces based on a fast level set method and the Chan-Vese model. We called it optimizing Chan-Vese model (OCV). This new algorithm is fast because it needs no re-initialization procedure and thus is suitable for fruit sorting. OCV has three advantages compared to traditional methods. First, it provides a unified framework for detection fruit shape boundary, requiring no preprocessing and even if the raw image is noisy or blurred. Second, it can detect boundaries for images of fruit with multi-colored edges, which traditional methods fail to deal with. Third, it is processed directly in colour space without any transformations that can lose much information. The proposed method has been applied to fruit shape detection with promising results.

Citation Download Citation

Zhouxiang Shou, Qihui Wang, Jiangsheng Gui, and Yuhuai Wang "Fruit shape detection by optimizing Chan-Vese model", Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74950W (30 October 2009); https://doi.org/10.1117/12.832308

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

RGB color model

Machine vision

Inspection

Edge detection

Image segmentation

Visual process modeling

Image analysis

Show All Keywords

Keywords/Phrases

Search In:

Publication Years