TY - GEN
T1 - A ground-truth fusion method for image segmentation evaluation
AU - Malladi, Sree Ramya S.P.
AU - Ram, Sundaresh
AU - Rodriguez, Jeffrey J
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/9/21
Y1 - 2018/9/21
N2 - Image segmentation evaluation is popularly categorized into two different approaches based on whether the evaluation uses a human expert's manual segmentation as a reference or not. When comparing automated segmentation against manual segmentation, also referred to as the ground-truth segmentation, multiple ground-truths are usually available. Much research has been done on analysis of segmentation algorithms and performance metrics, but very little study has been done on analyzing techniques for ground-truth fusion from multiple ground-truth segmentations. We propose a hybrid ground-truth fusion technique for image segmentation evaluation and compare it with other existing ground-truth fusion methods on a data set having multiple ground-truths at various coarseness levels. Qualitative and quantitative results show that the proposed method provides improved segmentation evaluation performance.
AB - Image segmentation evaluation is popularly categorized into two different approaches based on whether the evaluation uses a human expert's manual segmentation as a reference or not. When comparing automated segmentation against manual segmentation, also referred to as the ground-truth segmentation, multiple ground-truths are usually available. Much research has been done on analysis of segmentation algorithms and performance metrics, but very little study has been done on analyzing techniques for ground-truth fusion from multiple ground-truth segmentations. We propose a hybrid ground-truth fusion technique for image segmentation evaluation and compare it with other existing ground-truth fusion methods on a data set having multiple ground-truths at various coarseness levels. Qualitative and quantitative results show that the proposed method provides improved segmentation evaluation performance.
KW - Ground-truth
KW - evaluation
KW - fusion
KW - segmentation
UR - http://www.scopus.com/inward/record.url?scp=85055585920&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85055585920&partnerID=8YFLogxK
U2 - 10.1109/SSIAI.2018.8470317
DO - 10.1109/SSIAI.2018.8470317
M3 - Conference contribution
AN - SCOPUS:85055585920
T3 - Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation
SP - 137
EP - 140
BT - 2018 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2018
Y2 - 8 April 2018 through 10 April 2018
ER -