I think that all images on a macro level can be deconstructed and categorized by what is actually in an image. When iPhoto first popped up a recommendation of if I wanted to tag my friends by facial structure, I thought it was unbelievable. This is my page where I hope to learn more about the technical capabilities of segmentation of images.
Image retrieval
An image retrieval system is a computer system for browsing, searching and retrieving images from a large database of digital images. Most traditional and common methods of image retrieval utilize some method of adding metadata such as captioning, keywords, or descriptions to the images so that retrieval can be performed over the annotation words. Manual image annotation is time-consuming, laborious and expensive; to address this, there has been a large amount of research done on automatic image annotation. Additionally, the increase in social web applications and the semantic web have inspired the development of several web-based image annotation tools.
http://en.wikipedia.org/wiki/Image_retrieval
 CBIR
Content-based image retrieval (CBIR), also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR) is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases. (see this survey[1] for a recent scientific overview of the CBIR field). Content based image retrieval is opposed to concept based approaches (see concept based image indexing).
"Content-based" means that the search will analyze the actual contents of the image rather than the metadata such as keywords, tags, and/or descriptions associated with the image. The term 'content' in this context might refer to colors, shapes, textures, or any other information that can be derived from the image itself. CBIR is desirable because most web based image search engines rely purely on metadata and this produces a lot of garbage in the results.[clarification needed] Also having humans manually enter keywords for images in a large database can be inefficient, expensive and may not capture every keyword that describes the image.[citation needed] Thus a system that can filter images based on their content would provide better indexing and return more accurate results.[citation needed]
Adaptive Clustering Algorithm