The Study on Image Retrieval Technology Based on Salient Image Features

• Main Authors: Chieh-Hsien Lu, 呂皆賢
• Other Authors: Kuo-Lung Hung
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/92281552741094481971

碩士 === 朝陽科技大學 === 資訊管理系碩士班 === 99 === In recent years, with the development of information technology, There have an increasing demand for image processing. More and more media information with digital form is used in our everyday life. Now, to acquire or to generate digital images are very easy, but how to quickly and accurately meet the requirements to find the image in large image databases, is a intensive topic for further studies. In general, content-based image retrieval technology mainly includes the following two steps for image retrieval: first is the extracting features for each image and to store them in the feature database. The second step is to provide query by image to the system; to calculate similarity by the characteristics with the database features for each image and to identify the most similar images which are return back to the user. This research presents a significant image feature retrieval technology (Salient Point and Multi-features Descriptor based Image Retrieval Method, SMFD), The feature points are first detected by Harris corner to identify the features of image, and then the characteristics of the same color are formed to resist geometric attacks. The characteristics are the saturation, brightness, the average and, variance, the number of occurrences and the degree of the same color gathered. By matching feature regions through calculating the similarity, the similar images are return to the user. In the experimental results, different types of animals and the Caltech 101 face databases have been tested. As a result, the image retrieval precision and recall results are good, so this method can retrieve similar images of a image databases effectively.