With billions of images indexed in Google and other image search engines, how does Google choose images for search results? Many of the basics still apply.
Image ALT Attributes
When you hover over an image you see the image attributes, these attributes are used when a visually impaired person searches the Internet and need audio explanation about a picture. SEO professionals recommend that images offer a full description for the visually impaired and include keywords that help explain how the image should rank in search results.
Of course standard SEO best practices apply. Make sure the title and description of the image are optimized and follow SEO best practices. Save the image with a file name that includes the keywords that you want to rank on, and use underscores between words. Underscores will assist the search spider in separating words in the file name and the use of underscores will allow the file to resolve on both PC and Mac computers.
Image Quality and Resolution
Many times the higher the image quality the better a photo will rank. People that are looking for images want a picture that looks good.
Visual Facial Recognition
Google is beginning to look into facial recognition to choose the best image out of the many images indexed on the Internet. Search engineers agree that profile photos and pictures of individuals are much easier to sort through and find the most accurate image. Also easy to identify is well-known art including the Mona Lisa.
How will image search engines choose an image to rank prominently in image search that is not a profile photo or image of a famous painting? Similar to facial recognition and finger-print software, images will be broken into unique sections and compared to thousands of other similar images that have similar title, descriptions and ALT attributes. The image search engine will choose the image with the most unique attributes based on the similarities to other images with similar visual attributes.
This is of course a theory put forth by Google search engineers. You can expect that this type of image attribute recognition is going to be implemented into image search results, if not already.