Abstract book (pdf) - ICPR 2010

09:00-11:10, Paper WeAT8.29
Multi-Spectral Satellite Image Registration using Scale-Restricted SURF
Teke, Mustafa, Middle East Tech. Univ.
Temizel, Alptekin, Middle East Tech. Univ.
Satellites generally have arrays of sensors having different resolution and wavelength parameters. For some applications,
images acquired from different viewpoints and positions are required to be aligned. This alignment process could be
achieved by matching the image features followed by image registration. In this paper registration of multispectral satellite
images using Speeded Up Robust Features (SURF) method is examined. The performance of SURF for registration of
high resolution satellite images captured at different bands is evaluated. Scale restriction (SR) method, which has recently
been proposed for SIFT, is adapted to SURF to improve multispectral image registration performance. Matching performance
between different bands using SURF, U-SURF, SURF with SR and U-SURF with SR is tested and robustness of
these with respect to orientation and scale is evaluated.
09:00-11:10, Paper WeAT8.30
Automatic Attribute Threshold Selection for Blood Vessel Enhancement
Kiwanuka, Fred Noah, Univ. of Groningen
Wilkinson, Michael H.f., Univ. of Groningen
Attribute filters allow enhancement and extraction of features without distorting their borders, and never introduce new
image features. These are highly desirable properties in biomedical imaging, where accurate shape analysis is paramount.
However, setting the attribute-threshold parameters has to date only been done manually. This paper explores simple, fast
and automated methods of computing attribute threshold parameters based on image segmentation, thresholding and data
clustering techniques. Though several techniques perform well on blood-vessel filtering, the choice of technique appears
to depend on the imaging mode.
09:00-11:10, Paper WeAT8.31
Initialisation-Free Active Contour Segmentation
Xie, Xianghua, Swansea Univ.
Mirmehdi, Majid, Univ. of Bristol
We present a region based active contour model which does not require any initialisation and is capable of modelling
multi-modal image regions. Its external force is based on statistically learning and grouping of image primitives in multiscale,
and its numerical solution is carried out using radial basis function interpolation and time dependent expansion
coefficient updating. The initialisation-free property makes it attractive to applications such as detecting unkown number
of objects with unkown topologies.
09:00-11:10, Paper WeAT8.32
On Clock Offset Estimation in Wireless Sensor Networks with Weibull Distributed Network Delays
Ahmad, Aitzaz, Texas A&M Univ. Coll. Station
Noor, Amina, Texas A&M Univ. Coll. Station
Serpedin, Erchin, Texas A&M Univ. Coll. Station
Nounou, Hazem, Texas A&M Univ.
Nounou, Mohamed, Texas A&M Univ.
We consider the problem of Maximum Likelihood (ML) estimation of clock parameters in a two-way timing exchange
scenario where the random delays assume a Weibull distribution, which represents a more generalized model. The ML estimate
of the clock offset for the case of exponential distribution was obtained earlier. Moreover, it was reported that when
the fixed delay is known, MLE is not unique. We determine the uniformly minimum variance unbiased (UMVU) estimators
for exponential distribution under such a scenario and produce biased estimators having lower MSE than UMVU for all
values of clock offset. We then consider the case when shape parameter is greater than one and reduce the corresponding
optimization problems to their equivalent convex forms, thus guaranteeing convergence to a global minimum.
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