A Multi-feature Optimization Approach to Object-Based Image Classification
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- Zhang Q., Izquierdo E. (2006) A Multi-feature Optimization Approach to Object-Based Image Classification. In: Sundaram H., Naphade M., Smith J.R., Rui Y. (eds) Image and Video Retrieval. CIVR 2006. Lecture Notes in Computer Science, vol 4071. Springer, Berlin, Heidelberg
This paper proposes a novel approach for the construction and use of multi-feature spaces in image classification. The proposed technique combines low-level descriptors and defines suitable metrics. It aims at representing and measuring similarity between semantically meaningful objects within the defined multi-feature space. The approach finds the best linear combination of predefined visual descriptor metrics using a Multi-Objective Optimization technique. The obtained metric is then used to fuse multiple non-linear descriptors is be achieved and applied in image classification.
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