Research on Ship Image Retrieval Based on BoVW Model under Hadoop Platform

Image data is one of the key data in the ship's navigation record. Ship scene reappearance depends on its efficient retrieval. Recently, the exponential growth of the number of images makes the traditional single-machine image retrieval method gradually show the problem of inefficiency. In this paper, the image retrieval method based on the Bag of Visual Words (BoVW) model under the Hadoop platform is proposed and the distributed image retrieval is realized. Firstly, this paper takes BoVW model as the research object. Based on the Hadoop platform, the construction method of traditional visual dictionary is improved and the word frequency vectors are weighted by Term Frequency-Inverse Document Frequency (TF-IDF). Then the inverted index is generated in parallel for image retrieval. Experimental results show this method doubled the efficiency of visual dictionary construction while maintaining the original retrieval results and effectively improved the efficiency of image retrieval.