TY - JOUR
T1 - Visual quality evaluation of image object segmentation
T2 - subjective assessment and objective measure
AU - Shi, Ran
AU - Ngan, King Ngi
AU - Li, Songnan
AU - Paramesran, Raveendran
AU - Li, Hongliang
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/12
Y1 - 2015/12
N2 - A visual quality evaluation of image object segmentation as one member of the visual quality evaluation family has been studied over the years. Researchers aim at developing the objective measures that can evaluate the visual quality of object segmentation results in agreement with human quality judgments. It is also significant to construct a platform for evaluating the performance of the objective measures in order to analyze their pros and cons. In this paper, first, we present a novel subjective object segmentation visual quality database, in which a total of 255 segmentation results were evaluated by more than thirty human subjects. Then, we propose a novel full-reference objective measure for an object segmentation visual quality evaluation, which involves four human visual properties. Finally, our measure is compared with some state-of-the-art objective measures on our database. The experiment demonstrates that the proposed measure performs better in matching subjective judgments. Moreover, the database is available publicly for other researchers in the field to evaluate their measures.
AB - A visual quality evaluation of image object segmentation as one member of the visual quality evaluation family has been studied over the years. Researchers aim at developing the objective measures that can evaluate the visual quality of object segmentation results in agreement with human quality judgments. It is also significant to construct a platform for evaluating the performance of the objective measures in order to analyze their pros and cons. In this paper, first, we present a novel subjective object segmentation visual quality database, in which a total of 255 segmentation results were evaluated by more than thirty human subjects. Then, we propose a novel full-reference objective measure for an object segmentation visual quality evaluation, which involves four human visual properties. Finally, our measure is compared with some state-of-the-art objective measures on our database. The experiment demonstrates that the proposed measure performs better in matching subjective judgments. Moreover, the database is available publicly for other researchers in the field to evaluate their measures.
KW - Object segmentation
KW - objective measure
KW - subjective evaluation
KW - visual quality
UR - http://www.scopus.com/inward/record.url?scp=84959459099&partnerID=8YFLogxK
U2 - 10.1109/TIP.2015.2473099
DO - 10.1109/TIP.2015.2473099
M3 - Article
C2 - 26316130
AN - SCOPUS:84959459099
SN - 1057-7149
VL - 24
SP - 5033
EP - 5045
JO - IEEE Transactions on Image Processing
JF - IEEE Transactions on Image Processing
IS - 12
ER -