Based on the monitoring of Satellite Remote Sensing Images, a lot of big progresses have been made in environment
analysis and researches about the schistosome snail breeding ground and the distribution of snails in marshland. This
paper focuses on the identification of the Schistosome snail individual goals. Based on the image segmentation, the
objects, including snails, are segmented from the background. Pattern features of the snails are extracted by calculating
the invariant moments of typical snails. By calculating the invariant moments parameter of objects to be recognized and
the Euclid distance of the feature parameters of swatches, the snail targets are identified. In the laboratory environment,
the recognizing rate can reach over 90% and it has robust in rotation, scaling and translation.
The steps can be described as follows:
Step 1, by gray level modification, noise elimination, edge sharpening and binarization, the objects are segmented
from the background.
Step 2, typical snails' boundary is extracted by contour tracking and the central moments are calculated.
Step 3, the central moments is normalized. The 7 invariant moments are calculated as the pattern features of the
snails.
Step 4, the boundaries of these objects are extracted by contour tracking and the central moments are calculated.
Step 5, the central moments of the objects are normalized and the 7 invariant moments of the are calculated.
Step 6, the Euclid distances of The 7 invariant moments between the objects and the typical snail are calculated.
The objects with small distance will be judged as snails and the objects with large distance will not be judged as snails.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
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.