Auto tagging on smart search internet

Abstract

The use of tagging is one of the most important and popular features of the second generation web development and design (Web 2.0). The key highlight of using a tag is to give a keyword or a term to a piece of information to describe the contents of object for images. With these tags organized, users can efficiently browse and search the information they may require using a search engine. However, tagging is often very time consuming and tedious to do especially on images. With over billions of images hosted on the internet and they are neither tagged nor described. These images cannot be searched or be used to find similar information as there is no metadata bind to it. And therefore information in the image could not be used effectively. As there is a strong growing number of images uploaded every day, this makes it ideal to develop a automated image tagging system. This system must be able to tag the images fairly accurately and efficiently to generate the result at real time. The proposed system with a prototype developed in my project makes use of the color histogram for a few customized comparison methods and the result will be discussed. This report highlights a process developed for image tagging. And the focus of the report is on the new color histogram module which is the main image processing part. The design, implementation and simulation result will be discussed in this report.