Abstrato

Retrieval Applications in Image Segmentation using Wavelets and CBIR Algorithm

Manimegalai.S, Senthil.T

Segmentation refers to the process of partitioning a digital image into multiple segments. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. Processing images for specific targets on a large scale has to handle various kinds of contents with regular processing steps. To segment objects in one image, using the dual multiScalE Graylevel mOrphological open and close recoNstructions (SEGON) algorithm. It can be used to build a BackGround (BG) gray-level variation mesh, which is to identify BG and object regions. Content-Based Image Retrieval (CBIR) was carried out to evaluate the object segmentation capability in dealing with large-scale database images. CBIR is a technique which uses visual contents to search image from large scale database. The object segmentation method can be extended to extract other image features, and new feature types can be incorporated into the algorithm to further improve the image retrieval performance.