TY - JOUR
AU1 - Kuniaki Kawabata
AU2 - Mutsunori Takahashi
AU3 - Kanako Saitoh
AU4 - Mitsuaki Sugahara
AU5 - Hajime Asama
AU6 - Taketoshi Mishima
AU7 - Masashi Miyano
AB - Purpose – The purpose of this paper is to propose a state discrimination for crystallization samples (droplets), the purpose of which is to discriminate between diffractable extracts (crystal) and other objects. Design/methodology/approach – The line feature from the image of the protein droplet was extracted and the state discriminated using a classifier based on line features. A support vector machine is used as the classifier. Findings – In order to verify the performance of the proposed method, the growth state was discriminated experimentally using the images taken by TERA, an automated crystallization system. The correction ratio was determined to exceed 80 percent. Originality/value – Contribution to automated evaluation process of the growth state of protein crystallization samples.
TI - Crystalline object evaluation by image processing
JF - Sensor Review
DO - 10.1108/02602280810856714
DA - 2008-03-28
UR - https://www.deepdyve.com/lp/emerald-publishing/crystalline-object-evaluation-by-image-processing-8XP0QI1gHP
SP - 143
EP - 149
VL - 28
IS - 2
DP - DeepDyve
ER -