TY - GEN
T1 - Automatic alignment and comparison on images of petri dishes containing cell colonies
AU - Alqahtani, Safar
AU - Barczak, Andre
AU - Reyes, Napoleon
AU - Susnjak, Teo
AU - Ganley, Austen
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/11/28
Y1 - 2016/11/28
N2 - This paper proposes a novel approach to comparing cell colony images taken at different times on a Petri dish. The objective is to provide an assistive tool for microbiologists to quantify the loss of cell colonies on two Petri dishes, by mapping cell colonies between a pair of images. This problem is highly non-trivial, as the shape, size and position of the corresponding colonies vary randomly. In addition, the cell colony images for comparison are taken at different times and from slightly different perspectives (i.e. effects of shearing), and this amplifies the complexity of the problem. Experiments show that approaches purely based on SIFT or SURF, or algorithms used in astronomy, do not perform well on the problem domain. We therefore introduce a new approach to addressing these problems. A novel iterative technique that combines triangulation algorithms with the RANSAC alignment algorithm is proposed. Through hundreds of experiments, we demonstrate the efficacy of the new algorithm in comparison to existing ones found in the literature.
AB - This paper proposes a novel approach to comparing cell colony images taken at different times on a Petri dish. The objective is to provide an assistive tool for microbiologists to quantify the loss of cell colonies on two Petri dishes, by mapping cell colonies between a pair of images. This problem is highly non-trivial, as the shape, size and position of the corresponding colonies vary randomly. In addition, the cell colony images for comparison are taken at different times and from slightly different perspectives (i.e. effects of shearing), and this amplifies the complexity of the problem. Experiments show that approaches purely based on SIFT or SURF, or algorithms used in astronomy, do not perform well on the problem domain. We therefore introduce a new approach to addressing these problems. A novel iterative technique that combines triangulation algorithms with the RANSAC alignment algorithm is proposed. Through hundreds of experiments, we demonstrate the efficacy of the new algorithm in comparison to existing ones found in the literature.
UR - http://www.scopus.com/inward/record.url?scp=85006867164&partnerID=8YFLogxK
U2 - 10.1109/IVCNZ.2015.7761512
DO - 10.1109/IVCNZ.2015.7761512
M3 - Conference contribution
AN - SCOPUS:85006867164
T3 - International Conference Image and Vision Computing New Zealand
BT - 2015 International Conference on Image and Vision Computing New Zealand, IVCNZ 2015
PB - IEEE Computer Society
T2 - 2015 International Conference on Image and Vision Computing New Zealand, IVCNZ 2015
Y2 - 23 November 2015 through 24 November 2015
ER -