We present a watershed-based algorithm in the analysis of light microscopic image for reticulocyte (RET), which will be
used in an automated recognition system for RET in peripheral blood. The original images, obtained by micrography, are
segmented by modified watershed algorithm and are recognized in term of gray entropy and area of connective area. In
the process of watershed algorithm, judgment conditions are controlled according to character of the image, besides, the
segmentation is performed by morphological subtraction. The algorithm was simulated with MATLAB software. It is
similar for automated and manual scoring and there is good correlation(r=0.956) between the methods, which is resulted
from 50 pieces of RET images. The result indicates that the algorithm for peripheral blood RETs is comparable to
conventional manual scoring, and it is superior in objectivity. This algorithm avoids time-consuming calculation such as
ultra-erosion and region-growth, which will speed up the computation consequentially.
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.