文档介绍：The Research on Image Retrieval Technology Based
Relevance Feedback
Abstract
With the development and application of multimedia technology and
technology, various resources on work e more and more richer. In order
to meet various application requirements, image retrieval gets more and more popular,
the image retrieval technology grows an important research subject.
To meet the users’ needs of image retrieval, content-based image retrieval in
image retrieval has e an important research in image retrieval, which starts to
extract color, texture, shape, space and other features from images, then match the
corresponding features between images from image library and the image user want to
retrieve, at last gives the same or similar images retrieved in contents to the user. It is
the core for content-based image retrieval, how to accurately express and use image
features achieving efficient image retrieval.
In content-based image retrieval system, the image’s contents are performed by
the color, texture information and some low-level features. However, these underlying
characteristics can not reflect the similarity of the high-level concepts in human visual
perceive. Based on image feature extraction and measurement, This paper researchs
the image retrieval based relevance feedback between the image bottom features and
high-level semantic gap. By the interactive between system and users, relevance
feedback is a technology through learning to improve the retrieval systerm’s
performance. This paper proposes a weighted distance method for relevance feedback
mechanism, and image’s weighted value is the standard deviation ratio of the feature
values between the images in the database and associated image user selected.
Making the relevance feedback technology applying for not only weight of
independence each other but also for the weight of incremental update. On the other
hand, the weights of feat