In the field of computer vision, image mosaicking is achieved using image features, such as textures, colors, and shapes
between corresponding images, or local descriptors representing neighborhoods of feature points extracted from
corresponding images. However, image mosaicking based on feature points has attracted more recent attention due to
the simplicity of the geometric transformation, regardless of distortion and differences in intensity generated by camera
motion in consecutive images. Yet, since most feature-point matching algorithms extract feature points using gray
values, identifying corresponding points becomes difficult in the case of changing illumination and images with a
similar intensity. Accordingly, to solve these problems, this paper proposes a method of image mosaicking based on
feature points using color information of images. Essentially, the digital values acquired from a real digital color camera
are converted to values of a virtual camera with distinct narrow bands. Values based on the surface reflectance and
invariant to the chromaticity of various illuminations are then derived from the virtual camera values and defined as
color-invariant values invariant to changing illuminations. The validity of these color-invariant values is verified in a
test using a Macbeth Color-Checker under simulated illuminations. The test also compares the proposed method using
the color-invariant values with the conventional SIFT algorithm. The accuracy of the matching between the feature
points extracted using the proposed method is increased, while image mosaicking using color information is also
achieved.
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