Integrated Image Recognition Engine for Automatic Decoder Selection
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Solution Overview
Problem
Current image recognition systems require users to manually select and execute specific decoders for different object types, limiting their ability to recognize various objects and requiring direct user intervention, especially when multiple objects are present in an image.
Innovation Solution
An integrated image searching system that uses image recognition technology to classify object types based on feature point extraction, automatically selects and drives the corresponding decoder, and decodes objects, enabling recognition across multiple types without user intervention, and provides an efficient search process by recommending objects with the highest recognition rate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple individual decoders are equipped in each terminal for different object types, then recognition capability for specific object types is improved, but device complexity increases and user operation becomes more difficult
Solution Approach 1:
The patent combines multiple individual decoders (barcode decoder, QR code decoder, facial recognition decoder, image recognition decoder) into a single integrated recognition engine. This integration allows the terminal to recognize various object types using one unified system rather than requiring separate decoders for each type, thereby reducing device complexity while maintaining comprehensive recognition capability.
Solution Approach 2:
The integrated recognition engine is designed to perform multiple recognition functions (barcode recognition, QR code recognition, facial recognition, general image recognition) within a single system. This multi-functional approach enables the terminal to handle diverse object types without requiring separate specialized decoders, resolving the contradiction between versatility and complexity.
2Measurement precision
If users manually select and execute specific decoders for different object types, then recognition accuracy for known object types is improved, but ease of operation deteriorates and user intervention is required
Solution Approach 1:
The integrated recognition engine automatically detects the type of object in the captured image and selects the appropriate decoding method without requiring user intervention. The system autonomously determines whether to apply barcode decoding, QR code decoding, facial recognition, or general image recognition based on the input image characteristics, thereby maintaining high recognition accuracy while significantly improving ease of operation.
Solution Approach 2:
The recognition system dynamically adapts its processing method based on the input image content. Rather than requiring static user selection of decoder types, the system automatically adjusts its recognition approach according to the detected object type, enabling accurate recognition while simplifying user interaction.
3Reliability
If individual decoders are used for each object type, then specialization for specific code types is improved, but integrated recognition across all object types deteriorates
Solution Approach 1:
The patent merges multiple specialized decoders into a single integrated recognition engine that maintains the reliability of each individual decoder while adding the versatility to handle all object types. The integrated engine selectively applies the appropriate decoding algorithm based on the detected object type, ensuring reliable recognition across barcodes, QR codes, facial images, and other objects within a unified system.
Data Source
AI summary
The present disclosure relates to an image searching system and method for searching by using images of objects. Images of objects which it is desired to search are input via a PC-based terminal equipped with a webcam or a smart phone and then the input object images are analyzed using image recognition technology based on feature point extraction such that types of code contained in the object images are categorized and a decoder matching the object type is automatically driven such that the object is read, and thus a search function is provided which allows integrated recognition of all objects regardless of the type of object and which is convenient for the user.