A Novel Approach for Classification of Indoor Scenes
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2015 by IJCTT Journal|
|Year of Publication : 2015|
|Authors : Gagandeep Kaur, Dr. Amandeep Verma|
|DOI : 10.14445/22312803/IJCTT-V23P123|
Gagandeep Kaur, Dr. Amandeep Verma "A Novel Approach for Classification of Indoor Scenes". International Journal of Computer Trends and Technology (IJCTT) V23(3):108-112, May 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Scene classification is recently growing area of research in computer vision. A variety of approaches has been proposed for scene classification. The literature addresses the issues involved in indoor scene classification. The segmentation based approaches suffer from poor performance of segmentation and object-based approaches involve series of complex tasks like segmentation, training a large number of classifier and recognition. In this study, a novel approach for classification of indoor scenes into multiple classes has been proposed. The proposed feature representation is entirely based on extracting structural properties of the scene images. The proposed method uses Gaussian filter in pre-processing phase to reduce noise from image followed by using morphological operations to extract edge features from image. The one-vs-all Support Vector Machines (SVM) learning model is employed for learning and classification. To test the performance of classification system, a database of five indoor classes i.e. bedroom, living room, dining room, office and kitchen has been taken from MIT-indoor dataset. The images have been taken under different under different illumination conditions and different viewpoints. The accuracy of 84% and sensitivity of 56% has been obtained for five indoor classes.
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Indoor Scene Classification, Structural properties, Morphological Gradient.