A fuzzy qualitative approach for scene classification

Scene classification has been studied extensively in the recent past. Most of the state-of-the-art solutions assumed that scene classes are mutually exclusive. However, this is not true as a scene image may belongs to multiple classes and different people are tend to respond inconsistently even giv...

Täydet tiedot

Bibliografiset tiedot
Päätekijät: Lim, C.H., Chan, C.S.
Aineistotyyppi: Conference or Workshop Item
Kieli:English
Julkaistu: 2012
Aiheet:
Linkit:http://eprints.um.edu.my/14091/1/426.pdf
Kuvaus
Yhteenveto:Scene classification has been studied extensively in the recent past. Most of the state-of-the-art solutions assumed that scene classes are mutually exclusive. However, this is not true as a scene image may belongs to multiple classes and different people are tend to respond inconsistently even given a same scene image. In this paper, we propose a fuzzy qualitative approach to address this problem. That is, we first adopted the fuzzy quantity space to model the training data. Secondly, we present a novel weight function, w to train a fuzzy qualitative scene model in the fuzzy qualitative states. Finally, we introduce fuzzy qualitative partition to perform the scene classification. Empirical results using a standard data set and a comparison with K-nearest neighbour has shown the effectiveness and robustness of the proposed method.