Method of grading sample

Image analysis – Applications

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Reexamination Certificate

active

07142693

ABSTRACT:
Method of grading a sample. An input color image of the sample, such as a sample of raw cotton, is obtained by a scanning technique. This image is first analyzed by an image segmentation module and a binary image where pixels of a first characteristic are marked as 0 (e.g. cotton lint) and non-lint pixels are marked as 1. In a following particle recognition module, the adjacent non-lint pixels are grouped together as particles, and the color, size, shape and edge strength for each particle are computed. The particle descriptions are analyzed and each particle is assigned a trash type, i.e. leaf, bark, grass, pepper trash or shadow. The data of leaf and pepper trash are analyzed by a leaf grading module and leaf grade is reported. The data of bark/grass are analyzed by a bark/grass grading module and the bark/grass grade is reported.

REFERENCES:
patent: 5125279 (1992-06-01), Anthony et al.
patent: 5130559 (1992-07-01), Leifeld et al.
patent: 5539515 (1996-07-01), Shofner et al.
patent: 6567538 (2003-05-01), Pelletier
patent: 6621915 (2003-09-01), Chen et al.
Michael A. Lieberman, Evaluation of Learning vector Quantization to classify cotton Trash, Mar. 1997, Opt. Engineering, 36(3) 914-921.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Method of grading sample does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Method of grading sample, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Method of grading sample will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-3671116

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.