Image Recognition Indexing for Planogram Compliance
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Solution Overview
Problem
Existing methods for monitoring planogram compliance in retail environments are labor-intensive and inefficient, particularly in non-retail settings like warehouses, due to difficulties in accurately identifying products using manual tracking or RFID tags, and challenges with autofocus mechanisms in image capture systems.
Innovation Solution
A system and method utilizing an image recognition application that crops, scales, blurs, and brightens images of products to improve identification, generating a planogram and analyzing inventory changes, with features indexed in a k-D tree for efficient retrieval and compliance monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracking or RFID tags are used to monitor planogram compliance, then product identification can be achieved, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The patent uses image capture to create visual copies of products on shelves, replacing physical RFID tagging. The system captures images of products and uses image recognition algorithms to identify and track products automatically, eliminating the need for manual RFID tag attachment and reducing labor time while maintaining identification accuracy
Solution Approach 2:
The patent replaces manual mechanical processes (hand-placing RFID tags, physical inventory counting) with automated optical systems. Camera-based image capture and computer vision algorithms automatically identify products and monitor compliance, substituting human labor with automated imaging and processing systems
2Measurement precision
If autofocus mechanism is used in camera to capture product images, then one object can be focused clearly, but other objects at different distances become blurred
Solution Approach 1:
The patent processes multiple images captured at different focus distances and segments the analysis by identifying and extracting features from each image separately. The system captures a series of images with varying focus and processes them individually to recover information from all products regardless of their distance from the camera
Solution Approach 2:
The patent performs preliminary image processing operations including deblurring and feature extraction on captured images before final product identification. By pre-processing the images to restore focus information and extract key features early in the pipeline, the system recovers information from blurred regions that would otherwise be lost
Data Source
AI summary
The disclosure includes a system and method for indexing synthetically modified images of a high quality image. An image recognition application receives images of a product, crops background regions from the images, scales the image based on a minimum value among width and height of the image and generates multiple image sizes, blurs the images, brightens the image and indexes the images as being associated with the product. The images can be of box-shaped packages that include four or six images or cylindrical packages that include, for example, eight images of the packages. The images can be indexed in a k-dimensional tree for faster retrieval.