Paper Title
Red Tidealgae Recognitionusinghierarchical Level Abstraction Based on Semantic Feature

Abstract
The study of automatic red tide image recognition is not enough since the recognizing harmful algae image is difficult because over 200 species of algae in the world have a different size and features. In order to resolve the above limitation, this paper proposes the red tide algae image recognition method using hierarchical level abstraction approach based on semantic feature of NMF (nonnegative matrix factorization). The experimental results demonstrate that the proposed method achieves better performance than other red tide recognition methods. Keywords - Red Tide Algae, Image recognition, Low-level Abstraction, High-level Abstraction, NMF (nonnegative matrix factorization), Semantic Feature.