The internet has made it easier than ever before to search for products or specific forms of information, however, this has generally been in relation to keyword matches or other forms of semantic processing. Although these types of request have provided people with important tools for combing through the vast amounts of data that are available online the flexibility of such methods has left these tools with a lack of functionality. For this reason, the ability to do visual searches through image recognition has become an important concept in modern computing. Rather than using words or phrases as search terms, visual searches would provide users with the ability to upload an image or snapshot and receive related feedback based on the discernible qualities that it contains. This would dramatically alter the way in which people communicate, shop, or seek out information.
While there are are various software tools that have been developed for such purposes, the underlying algorithms that they use in order to achieve such capabilities can result in dramatically different results. Image recognition capabilities depend on the ability to recognize, identify, and detect specific forms of information that can then be related to other similar items. For this reason, acquisition, processing, and decision making are all largely dependent on how the program itself has been constructed. Furthermore, the models for hardware that these systems are distributed under can also impact the way that they are implemented in the real world. The widespread availability of smartphones and other high-end devices provides the necessary market for such software to be distributed to consumers in a quick and effective manner. The need for advanced predictive models and flexibly adaptive methods for data extraction demonstrate the need for developers to find new and creative ways to achieve these goals.
Slyce, a visual search and recognition company, created the universal scanner out of their desire to develop an effective way to apply image recognition to the mobile world. The primary motive of the software is to allow people to simply snap a picture of an item or product and be given quick and accurate results for similarity. Furthermore, the application merges this functionality with pre-existing technologies such as QR code and coupon readers in order to provide consumers with a single, efficient, and incredibly useful package that is able to process real world images for use in the online realm. The ability to discover, organize, and purchase items through a single unified setting demonstrates the capabilities that image recognition has for both buyers and sellers alike.