Image Recognition Apparatus Code Priority Processing
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Solution Overview
Problem
Image recognition apparatuses face challenges in reducing the processing time required for object recognition, which is typically lengthy and inefficient.
Innovation Solution
The apparatus employs a processor with a memory and interface to store identification and image information, using code recognition initially and switching to object recognition if code recognition fails, thereby optimizing processing by executing code recognition first, which is faster, and then performing object recognition only when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If object recognition is performed using image information comparison, then recognition accuracy is improved, but processing time increases
Solution Approach 1:
The patent segments the image into multiple regions of interest (ROIs) and processes each region independently. By dividing the image into candidate object regions and background regions, the system can focus computational resources on specific areas, reducing overall processing time while maintaining recognition accuracy through targeted analysis of each segment.
Solution Approach 2:
The patent performs preliminary processing by generating candidate object regions and creating region-of-interest masks before detailed object recognition. This preliminary segmentation and preprocessing step prepares the data in advance, allowing the main recognition algorithm to work more efficiently on pre-processed information, thus reducing total processing time.
2Productivity
If code recognition is performed first, then processing speed is improved, but system complexity increases
Solution Approach 1:
The patent implements a dynamic, multi-stage recognition system that adapts its processing approach based on the situation. The system first attempts code recognition for quick identification, and only transitions to full object recognition when code recognition fails or is insufficient. This dynamic switching optimizes processing speed while managing system complexity through conditional execution of different recognition algorithms.
Data Source
AI summary
An image recognition apparatus includes a memory, an interface and a processor. The memory stores identification information obtained from code information attached to the objects and image information on the objects used for object recognition, the storage storing the identification information and the image information for each of objects to be recognized. The processor which controls to: extract a target object region including an object therein from a photographed image; extract code information in the target object region and recognize the identification information based on extracted code information; and recognize the object based on an image of the target object region and image information on each object, if the processor fails to recognize the object based on the code information.