Pictures often are informational gold, conveying in a mere blink what it might take paragraphs or even pages to explain. Subsequently, visual content has flooded the Internet. Widespread availability alone, however, doesn’t guarantee usefulness. To get that, you have to have a way to sift through the content easily, which is where image search comes in.
Just what is visual search, anyway?
Visual search is a way of looking up and retrieving a visually similar images. When a picture is uploaded to the server, algorithms run that within an application that checks for visual consistencies. The algorithm is very sophisticated and can find similarities between images by analyzing them and finding similar patterns. One huge benefit of this technology, because its all online, you can look for images anywhere you have a reliable Internet connection on any Web-ready device. They also typically contain a significantly higher number of images than application-based image databases and allow you to search a wide range of images.
Okay, but how does visual search actually work?
All visual searches start with a query or request. Traditionally, with text based search, you type a word or phrase into a search box. With visual search, everything starts with either a photo being uploaded or taken from a smart phone. The system then analyzes the images in the database to find ones that match what you’re searching for. The analysis often looks at patterns and similarities in the images, which is then paired up with other related images which are then shown to the user. The system retrieves the images it can, ranking them based on how closely the query matches the analysis results.
What are the latest innovations in visual search?
Visual search involves a process known as indexing. This is where everything that goes into the database gets classified or labeled so that they are grouped together and can be found quickly. It’s not much different than the indexes at the end of books that tell you what pages contain specific information. In the end, indexing allows the system to speed up the search process, but traditional indexing still requires manual work, which is costly and time-consuming.
To overcome these hurdles, companies are developing more advanced ways of performing image searches. One of these is Superfish, a company based in Palo Alto, California. It has developed applications that, using sophisticated algorithms, can retrieve images based on visual rather than textural elements, such as geometric features. Query submissions are images uploaded by users. Once the system has retrieved some results from the database, it continues to fine tune the results based on the images the user clicks on.
The new methods of image-to image or visual search companies like Superfish are creating have a huge range of potential applications. They allow you to shop online by what you see, for example, quickly finding and comparing similar products. Compatible with many mobile devices, they can be useful in other areas such as academics, business presentations or documentation or even Internet dating or crafts. Superfish hopes that the systems will produce a radical shift in the way people work with and share visual content overall.
Visual Search is a basic way for you to find pictures from a database. It’s often used in conjunction with the Internet. Rapid shifts in visaul search technology promise to transform how everyday users can find the pictures they’re looking for, so watching what companies like Superfish are doing can prepare you for new, easier ways of working with visual content.