The ability to recognize objects is a fundamental human trait, one that begins developing from birth. As infants we learned to observe and absorb details about the world, such as shape, color, and texture, using both sight and touch. This early exploration laid the foundation for our understanding of the world, enabling us to effortlessly recognize familiar objects as we grow. Whether walking outdoors, watching a movie, or reading this article, recognizing objects has become second nature.
Recognizing Products in a Retail Environment
This same process of recognition occurs when we shop for groceries. We look at our shopping list, and then quickly scan the shelves for visual clues for this specific item. For example, when looking for oranges in the produce section, we use mental reference points such as color, size, and shape to differentiate between varieties like mandarins, mineolas, and oranges. However, when it comes to apples, the task becomes more challenging due to the wide variety of available options. While most stores offer only a subset of these varieties, selecting the correct one can still prove difficult. Even for experienced store staff, it is often hard to find the right variety in the POS system.
Item Recognition and Self-Checkout Solutions
Item recognition, particularly for fresh produce like vegetables and fruits, is often seen as a complicating factor for self-checkout solutions. Shoppers must select the correct item, weigh it, and add it to their transaction. It’s a complex and time-consuming task that leads to shopper frustrations, longer wait times and mistakes on the receipt.
Leveraging Smart Vision Technology for Enhanced Recognition
Advanced technology now provide a solution to this issue. With 3D cameras and deep-learning algorithms powered by AI, smart vision technology has made it easier for customers to identify and purchase fresh produce without barcodes. The process is straightforward: customers place their fresh produce item on a scale-equipped with a camera, which then recognizes the item.
Smart vision technology recognizes the item - and after the customer's approval - the item is added to the transaction with a single click. This simplifies the checkout process for customers while minimizing the need for staff intervention in correcting mislabeled fresh items. With smart vision technology, consumer frustration can be replaced by a better shopping experience and more transactional efficiency.
Item Recognition for Non-grocery Items
Smart vision technology is also applicable in areas other than fresh produce. For instance, IKEA, a leading furniture retailer, uses camera-equipped self-checkout solutions. A camera mounted on the checkout device detects any scanning errors, prompting the customer to rescan and correct the items in their basket if necessary. IKEA has deployed this automatic item recognition technology in several European countries. This solution, powered by an open-API software platform, improves the self-checkout experience by enabling scan-and-go functionality, reducing queues, and minimizing friction. It highlights how AI-driven smart vision technology can improve the customer experiences by eliminating frictions and reducing queues.
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