I’ve long been a fan of the concept of image recognition, especially in terms of mobile marketing and the potential it has when combined with today’s feature-packed smartphones.  Problem is, several underlying technologies needed for mainstream image recognition have been either under-developed or simply non-existent.

With Google’s debut of its new Goggles visual search app, many of those barriers have been overcome.  The concept of Google Goggles is dead simple- a user snaps a photo of an object around them, be it a book, building, text or any other object, and the app will return search results tailored for that object.  Snap a photo of a book you’re interested in, for example, and goggles will return reviews, table of contents, links to purchase the book and anything else residing in Google’s index that might be relevant.

Granted, this type of thing has been around for quite some time, from several startups, but the difference here is the fact that Google’s enormous index is the centerpiece- an attribute that no startup in the image recognition space has ever had.

To be able to return results for real-world objects on a large scale, you have to have as much data related to those objects as possible.  No one has access to as much data as Google, and bringing visual search and mobile image recognition to the masses, realistically speaking, is a step forward only Google can make.  Even for a company like Google however, it won’t be easy.

Google’s Marrisa Mayer was asked today at the Le Web conference in Paris how far away Google truly is from bringing the concept mainstream, and she admitted there’s a long way to go.  ”Google Goggles is partly indexing, but it’s mainly image recognition combined with elements of location and OCR,” she explained.  ”As these technologies evolve, so will we.  At this point, voice to text is further along than image and video recognition technology, so we’re at the starting line now.

Image recognition and visual search are concepts that will be undeniably huge for mobile marketing.  As more and more consumers start snapping photos of real-world, everyday objects around them in an attempt to learn more about those objects, it provides a perfect opportunity for any mobile marketer to step-in and provide their own tailored result for those objects.  Especially on a local level.

With mobile image recognition, the aspects of opt-in compliance and user privacy are more or less void given the fact that the end-user makes the first move instead of the advertiser.  Instead of pushing messages and other content to mobile users in an attempt to solicit a response, the user snaps the photo and is directed to your content on their own.

One thing is for sure, when visual search and image recognition do become mainstream, every mobile marketer better have a gameplan.