Research Of Retrieval Technology Based On Natural Language In Image Database

Natural language is an effective tool to express ideas. It is a sententious and effective method to express the semantic information of images. Natural language-based image retrieval (NLBIR) is a technique for searching images on the basis of image semantic features and the content of image .The image semantic features mean what the image express, while the image content features are the low-level visual features, which include image color, image background, image bodies which are described by body direction, body size and body position etc.There are two key issues in the NLBIR. One is how to extract key semantic information from the Chinese sentences. The other is how to match query and stored images in away that reflects human similarity judgement.On the basis of researching the word segmentation characteristics and methods of the Chinese language, the paper refers to the word-stocks and Dynamic-Link Libraries in order to realize word segmentation of Chinese sentence automatically, and then extract key semantic information from the sentence. What' s more the paper transforms the color words in the key information into HIS values that can be measured. The HIS values are the basis of calculating the color similarity of the query and stored images.According to different attributes, different similarity measuring methods are adopted. When calculating main colors similarity of two images, the frequencies of colors are considered. The object size of one image is expressed as proportion of the area of object and the area of image. There are three kinds of object size such as large, middle, small. The paper takes different method to gain the object size similarity according to their different character and target image. The object position similarity is calculated on the basis of the distance of two positions. Some method is taken to make the distance less than 1.0. The object direction similarity is calculated on the basis of objects' angledifference. The paper takes climax to calculate the whole similarity of two images because we take hiberarchy to express one image.To scale the complexity of one image' s description, the paper introduces a concept that is the information measurement. We also take climax to calculate the information measurement of one image. How to calculate the information measurement of one image' s attributes is a question that is value to discuss. The paper improves the Shannon method, and uses it in the compositor of retrieval outcomes.In similarity measurements mentioned above, one image searching system that is on the basis of natural language comprehension is designed. The system obtains perfect outcome by experiment proved. In the end, the further research direction is pointed out.