Browsing by Subject "Matching theory."

Now showing 1 - 4 of 4

Open Access
Feature point classification and matching
(2007) Ay, Avşar Polat
A feature point is a salient point which can be separated from its neighborhood. Widely used definitions assume that feature points are corners. However, some non-feature points also satisfy this assumption. Hence, non-feature points, which are highly undesired, are usually detected as feature points. Texture properties around detected points can be used to eliminate non-feature points by determining the distinctiveness of the detected points within their neighborhoods. There are many texture description methods, such as autoregressive models, Gibbs/Markov random field models, time-frequency transforms, etc. To increase the performance of feature point related applications, two new feature point descriptors are proposed, and used in non-feature point elimination and feature point sorting-matching. To have a computationally feasible descriptor algorithm, a single image resolution scale is selected for analyzing the texture properties around the detected points. To create a scale-space, wavelet decomposition is applied to the given images and neighborhood scale-spaces are formed for every detected point. The analysis scale of a point is selected according to the changes in the kurtosis values of histograms which are extracted from the neighborhood scale-space. By using descriptors, the detected non-feature points are eliminated, feature points are sorted and with inclusion of conventional descriptors feature points are matched. According to the scores obtained in the experiments, the proposed detection-matching scheme performs more reliable than the Harris detector gray-level patch matching scheme. However, SIFT detection-matching scheme performs better than the proposed scheme.
Open Access
Line segment based range scan matching without pose information for indoor environments
(2008) Yakın, İskender
A mobile robot exploring an unknown environment often needs to keep track of its pose through its sensors. Range scan matching is a way of computing the pose difference of a robot at two different locations on the navigation path by finding common features observed in range sensor readings recorded at these locations. In this thesis, we introduce a new algorithm which computes this pose difference by matching common line segments extracted from two laser range scans taken from two different but unknown poses. In this algorithm, matching is performed by exploiting invariant geometric relations among line segments. The use of line segments instead of range points also reduces the computational complexity of determining the pose difference between two distinct scans. Compared to other scan matching algorithms, our method presents a powerful means for global scan matching, map building, place recognition, loop closing and multirobot mapping, all in real-time.
Open Access
Turkish factoid question answering using answer pattern matching
(2009) Pala Er, Nagehan
Efficiently locating information on the Web has become one of the most important challenges in the last decade. The Web Search Engines have been used to locate the documents containing the required information. However, in many situations a user wants a particular piece of information rather than a document set. Question Answering (QA) systems have addressed this problem and they return explicit answers to questions rather than set of documents. Questions addressed by QA systems can be categorized into five categories: factoid, list, definition, complex, and speculative questions. A factoid question has exactly one correct answer, and the answer is mostly a named entity like person, date, or location. In this thesis, we develop a pattern matching approach for a Turkish Factoid QA system. In TREC-10 QA track, most of the question answering systems used sophisticated linguistic tools. However, the best performing system at the track used only an extensive list of surface patterns; therefore, we decided to investigate the potential of answer pattern matching approach for our Turkish Factoid QA system. We try different methods for answer pattern extraction such as stemming and named entity tagging. We also investigate query expansion by using answer patterns. Several experiments have been performed to evaluate the performance of the system. Compared with the results of the other factoid QA systems, our methods have achieved good results. The results of the experiments show that named entity tagging improves the performance of the system.
Open Access
Wage implications of foreign direct investment with salary adjustment process
(2012) Özcan, Elif
The main objective of this thesis is to analyse theoretically the implications of increasing foreign direct investment (FDI) on the wages of workers and on the profits of firms in the local country which is previously studied in Saglam and Sayek (2011). In this study, we modify the Kelso and Crawford’s salary adjustment process. Firstly, capacity constraint of firms is introduced into the Kelso and Crawford’s salary adjustment process. Secondly, we study the process where workers make offers. Existence of stable matching is explored. In the process where firms offer, the matching converges to a stable matching but in the process where workers offer, stability may not hold. While analysing the implications of increasing FDI on the wages and on the profits in the local country, we use the firm-proposing salary adjustment process with capacity constraint. Our analysis shows that under certain assumptions workers and foreign firms benefit from increasing presence of foreign direct investment while domestic firms may lose profits.