Brightness-invariant image segmentation for on-line fruit defect detection

James Zhiqing Wen; Yang Tao

doi:10.1117/1.601882

1 November 1998 Brightness-invariant image segmentation for on-line fruit defect detection

James Zhiqing Wen, Yang Tao

Optical Engineering, Vol. 37, Issue 11, (November 1998). https://doi.org/10.1117/1.601882

The extraction of defective segments from fruit images is a critical step for on-line fruit defect detection using machine vision. To accommodate the gradient reflectance characteristics of objects with curved surfaces such as apples and to avoid the defect inspection error due to the natural brightness variability of fruit, a novel and practical brightness-invariant image segmentation method is developed. Experimental results from our vision-sorting system show that the proposed method is effective for large-scale multiple-line processing of massive numbers of apples.

Citation Download Citation

James Zhiqing Wen and Yang Tao "Brightness-invariant image segmentation for on-line fruit defect detection," Optical Engineering 37(11), (1 November 1998). https://doi.org/10.1117/1.601882

Published: 1 November 1998

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