Fuzzy sets, decision making and expert systems
Fuzzy sets, decision making and expert systems
Automatic object extraction from aerial imagery—a survey focusing on buildings
Computer Vision and Image Understanding
Coordinate logic filters: theory and applications in image analysis
Nonlinear image processing
SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Projective geometry and photometry for object detection and delineation
Projective geometry and photometry for object detection and delineation
Combining low-level features for semantic extraction in image retrieval
EURASIP Journal on Advances in Signal Processing
FCTH: Fuzzy Color and Texture Histogram - A Low Level Feature for Accurate Image Retrieval
WIAMIS '08 Proceedings of the 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services
A hybrid scheme for fast and accurate image retrieval based on color descriptors
ASC '07 Proceedings of The Eleventh IASTED International Conference on Artificial Intelligence and Soft Computing
CEDD: color and edge directivity descriptor: a compact descriptor for image indexing and retrieval
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Man-made structure detection in natural images using a causal multiscale random field
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
A multi-feature optimization approach to object-based image classification
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
IEEE Transactions on Circuits and Systems for Video Technology
| Hi-index | 0.00 |
The paper presents a hybrid approach that ultilizes multiple low-level feature descriptors for performing building detection in 2D images. The proposed method is a symbiosis of two feature descriptors, namely Color and Edge Directivity Descriptor (CEDD) and Fuzzy Color and Texture Histrogram (FCTH). The use of edge detection, texture and color combined features using fuzzy technique in encoding low-level visual information from images are embedded in the hybridization. First, multiple locations from a target image are chosen in the feature extraction process. Then, a hybridized vector index is proposed for measuring the low-level visual features distance between the target natural images with the training images, allowing a building content to be detected. Size and resolution of the source of images are not restricted in the proposed model and thus it can enhance the computational effectiveness. The empirical assessment, in term of the accuracy in detecting building objects in a set of images, validates the feasibility and potentiality of the proposed techniques.