Digital Signal Processing Reference
In-Depth Information
Chapter 2
Image Segmentation with Eigen-Subspace
Projections
Jar-Ferr Yang and Shu-Sheng Hao
Abstract
In this chapter, object segmentation algorithms dependent on the
characteristics of eigen-structure are proposed. The eigen-subspaces are obtained
from eigen-decomposition of the covariance matrix, which is computed from the
selected color samples. Hence, the color space can be transformed into the signal
subspace and its orthogonal noise subspaces. After statistical analysis of eigen-
structure of target color samples, the color eigen-structure segmentation algorithms
are then designed to extract the desired objects, which are close to the color sam-
ples. The principal component transformation (PCT) techniques, which only use
the signal subspace can be treated as a subset of color eigenspace algorithms. The
eigenspaces discriminated as signal and noise subspaces related to original color
samples should be effectively utilized. The adaptive eigen-subspace segmentation
(AESS) algorithm, which can save the computation of eigen-decomposition, is
applied to adaptively adjust the eigen-subspaces. Finally, the Eigen-based fuzzy
C-means (FCM) clustering algorithm has been proposed to effective segment color
object. By jointly consideration of signal and noise subspace projections of de-
sired colors, the separate eigen-based FCM (SEFCM) and coupled eigen-based
FCM (CEFCM) are used to achieve effective color object segmentation. With
these proposed algorithms, the color objects can be successfully extracted by using
eigen-subspace projections.
2.1
Overview
Image segmentation has been treated as a key technology in many smart image and
video related applications. To achieve effective coding, for example, the image seg-
mentation is the most important kernel in construction of the MPEG-4 video object
plane (VOP) [
1
,
2
]. The four major features, including luminance, motion, color,
J.-F. Yang (
)
Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan
e-mail:
jfyang@ee.ncku.edu.tw
