Most change detection methods are based on gray-level images.
A gray-level image is regarded as a 1-D projection
of three channels of color images. Therefore, more precise
change detection results are expected by utilizing color information.
We previously developed a change detection scheme
using color images. In this paper, we determine which color
space should be selected for accurate change detection based
on our previous detection scheme. Our method can be applied
to various color spaces, including gray-level images. Then we
can measure the expected number of error pixels in order to
select an appropriate color space which gives the best result
among various color spaces. The experiments show that selecting
a color space based on measurements results in the
fewest error pixels.
A gray-level image is regarded as a 1-D projection
of three channels of color images. Therefore, more precise
change detection results are expected by utilizing color information.
We previously developed a change detection scheme
using color images. In this paper, we determine which color
space should be selected for accurate change detection based
on our previous detection scheme. Our method can be applied
to various color spaces, including gray-level images. Then we
can measure the expected number of error pixels in order to
select an appropriate color space which gives the best result
among various color spaces. The experiments show that selecting
a color space based on measurements results in the
fewest error pixels.