In this paper an evaluation of image keypoints detectors and descriptors is presented
when used for building panoramic image. The descriptors: (SIFT, SURF, BRIEF, ORB,
BRISK, and FREAK) were discussed, when used with the appropriate keypoints detec
tors
on database taken indoors by RGB-D camera. Crosscheck and RANSAC (RANdom
Sample Consensus) algorithms were used to find transform matrix between images. The
speed of keypoints detectors and descriptors, the matching speed, the average of extracted
keypoints, recall and precision were investigated. Oxford dataset was used to find the best
descriptor for dealing with rotation and illumination changes that might occur due to
changes in illumination angle.
The obtained results showed that SIFT was the keypoint descriptor with the highest
performance in non-real time applications. The SURF/BRISK was the best
detector/descriptor which can be used in real time applications with comparable SIFT's
results.
Service Oriented Computing (SOC) is changing the way of developing software systems.
Each web service has a specific purpose to serve, so it can not satisfy users’ request.
In this paper, we propose a Web services composition method based on OWL on
tology,
and design an automatic system model for services discovery and composition. This
method uses domain ontology and WordNet to calculate matching between input and
output parameters and uses Category ontology to solve the problem of semantic
heterogeneity in web service description. We use services with single input and single
output and cost as QoS criteria. This method can enhance the efficiency and accuracy of
service composition, and the experiments are used to validate and analyze the proposed
system.
