期刊名称：International Journal of Computer Information Systems and Industrial Management Applications
印刷版ISSN：2150-7988
电子版ISSN：2150-7988
出版年度：2019
卷号：11
页码：142-150
出版社：Machine Intelligence Research Labs (MIR Labs)
摘要：In interactive segmentation, user inputs are required
to produce cues for the algorithms to extract the object of interest.
Different input types were recommended by the researchers in
their developed algorithms. The most common input types are
points, strokes and bounding box. Different evaluation
parameters were used in the researches in this field for
comparison. Our previous work shows that, for non-complex
image, segmentation result will not be affected by the user input
type used. Complex images are defined as images whereby the
colors of the objects of interest and the background are similar
and vice-versa. In some of the complex images, parts of the color
of the objects of interest are present in the background. This
paper extends our previous work by using the proposed unified
input types, which consists of a bounding box to locate the object
of interest range and a stroke for the foreground, on three
interactive segmentation algorithms for non-complex and
complex image. Three different evaluation measures are
computed to compare the segmentation quality: Variation of
Information (VI), Global Consistency Error (GCE) and Jaccard
index (JI). From the experiment results, it is noticed that, all
three algorithms perform well for non-complex images but could
not perform as good for complex images.
关键词：interactive segmentation; complex; non;complex; user
input; bounding box; stroke;
