Scene matching is of great interest in the pattern recognition and computer vision domain. Some researchers investigated the problem of scene matching, by employing phase correlation and neural network. Although varying good results have been obtained, noise and occlusion appear to affect the robustness of these matching algorithms. In order to develop a scene matching system that is robust to adverse condition (i.e. occlusion and added noise) and produces intuitively reasonable results, a robust scene matching system based on line segments is proposed in this paper. Since line pattern is effective for scene representation and matching, the proposed system employs a two-stage hierarchy, i.e. line segmentation and matching. In the first stage, the raw scenes are transformed into line segment maps (LSM); in the second stage, the Line Segment Hausdorff Distance (LHD) measure is applied to generate the matches. The line segmentation approach is based on robust shape feature and tends to generate more consistent LSM, while the LHD has the advantage to incorporate structural and spatial information to compute dissimilarity between two sets of line segments rather than two sets of points. Encouraging results have been obtained with aerial images.
The problem of logo recognition is of great interest in the document domain, especially for document database. By recognizing the logo we obtain semantic information about the document which may be useful in deciding whether or not to analyze the textual components. In order to develop a logo recognition method that is efficient to compute and product intuitively reasonable results, we investigate the Line Segment Hausdorff Distance on logo recognition. Researchers apply Hausdorff Distance to measure the dissimilarity of two point sets. It has been extended to match two sets of line segments. The new approach has the advantage to incorporate structural and spatial information to compute the dissimilarity. The added information can conceptually provide more and better distinctive capability for recognition. The proposed technique has been applied on line segments of logos with encouraging results that support the concept experimentally. This might imply a new way for logo recognition.
In order to solve the slowly modified rate of 1 Hz of a GPS and the infinite position error of an INS, a continuously high accurate positioning algorithm of a linear convex combination of a linear-two-point and a quadratic-five-point polynomial to filter and predict GPS and INS positioning data is presented in this paper. The integration experiment of real GPS data and simulated INS data has shown the validity of this method. It provides a new approach of continuously high accurate real-time positioning under medium or highly dynamic environment.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.