Abstract:

The water damage problem is more and more worse in recent years, so the problem of algae image  classification and retrieval is extremely urgent. To solve this problem the algorithm based on content is proposed. SIFT(Scale-invariant feature transform) algorithm is used to extract shape feature of algae image because marine biological image is color insensitive. The dimension of the feature vector generated by SIFT can reach up to 128. The higher dimensions can affect classification prediction and can lead to high computational complexity. PCA(Principal Component Analysis) technology is adopted to reduce the dimension of the feature avoiding dimension disaster. K-means is employed to clustering algorithm, which is simple and effective. The result of the clustering algorithm is packaged by Bag of Words in order to subsequent identification. KNN (K-Nearest Neighbors) algorithm is used to recognition. The experimental results are finally consistent with the fact. It provides effective support for the research of environmental problems which is caused by algae.

Key words: image classification, image retrieval, algae image, scale-invariant feature transform ( SIFT);
principal component analysis(PCA)