|Our system overview We input a photo to our system Result Input Photo Result Input photo Result||
In recent years, web services, such as ‘’Yahoo Image Search,’’ ‘’TinyEye,’’ ‘’ookaboo,’’ that provide image search engine have become popular. Benefiting from these image search engines, users can input their photos to find the pictures that contain similar object, therefore users can recognize the contents in the photos they uploaded. If the uploaded images happened to be building photos, we can develop a tourism system providing information for users. However, searching the building photos accurately is a challenge, due to the variation of lighting conditions, diverse viewpoints and varieties of textures, which affects the photo quality and searching results. In this thesis, we proposed an image search system that aims at searching building and landmark architectural photos. With taking at least 1024x768 resolution of color building image as an input, our system can find photos that contain similar or the same buildings from our database. We exploited a three-step method which combines color feature, Histogram of Oriented Gradient and Scale invariant feature transform to solve the problems. To improve the performance of searching speed, we use tree structure and string metric method to make our system more efficient.