Image-Based Application Activation via Flatness Detection
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Solution Overview
Problem
Information terminals like smartphones and tablets face challenges in efficiently activating applications due to overcrowded screens, where icons for various applications are spread across multiple pages, leading to increased time spent searching for the intended application, and existing solutions may inadvertently activate wrong applications based on detected images.
Innovation Solution
An information processing device and method that uses a camera to input image data, determines matching pre-registered images, computes image complexity, and executes specific processing when the image is determined to be flat, allowing for intentional activation of applications by reflecting user intentions through image-based instructions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of applications is increased, then functionality is improved, but screen space becomes insufficient and icon search time increases
Solution Approach 1:
The system pre-registers standard images (QR codes, barcodes, logos) and their corresponding application information in advance. When a user points the camera at such an image, the system can immediately activate the associated application without requiring the user to manually search through multiple pages of icons, thus reducing activation time while maintaining access to numerous applications.
Solution Approach 2:
The patent introduces an intermediary mechanism (image recognition system) between the user and the application activation process. Instead of directly interacting with icons on the screen, the user points the camera at an external image, and the system mediates by recognizing the image and automatically launching the corresponding application, thereby eliminating the need to search through crowded screens.
2Loss of time
If image-based activation is implemented, then activation speed is improved, but accidental activation of wrong applications may occur
Solution Approach 1:
The system provides feedback to the user by displaying the recognized image type and corresponding application information before activation. This allows the user to verify that the correct application will be activated, preventing accidental launches while maintaining fast activation speeds. The feedback loop ensures reliability by confirming the match between the scanned image and the intended application.
Solution Approach 2:
The system performs preliminary verification by matching the scanned image against pre-registered standard images and displaying the corresponding application information before execution. This preliminary action allows users to confirm the correctness of the recognition result, preventing accidental activation of wrong applications while maintaining rapid activation for correct matches.
3Ease of operation
If camera-based image input is used, then user interface convenience is improved, but detection precision may be reduced due to image quality variations
Solution Approach 1:
The system employs parameter changes by adjusting recognition thresholds and using multiple recognition methods (QR code recognition, barcode recognition, logo recognition) based on image characteristics. When image quality is high, more precise matching criteria are applied; when quality is lower, the system adapts by using multiple recognition approaches to maintain precision while preserving ease of operation.
Solution Approach 2:
The patent introduces an intermediary image processing system that mediates between the camera input and the recognition algorithm. This intermediary layer performs preprocessing, enhances image quality, and selects appropriate recognition methods based on image characteristics, thereby maintaining high detection precision even when camera-based input quality varies, while preserving the convenience of hands-free operation.
Data Source
AI summary
An image collation unit determines whether input image data matches pre-registered image data or a feature quantity of the input image data matches a pre-registered feature quantity of the image data, and stores in a memory at least one of input image data which is determined to match and information which represents the input image data. A complexity computing unit computes complexity of the image data. An image flatness determination unit determines, on the basis of the computed complexity of the image data, whether the image data is data which denotes a flat image. An information processing execution unit executes, when it is determined that newly input image data is data which denotes a flat image and the input image data or the information which represents the input image data is stored in the memory, information processing specified by the input image data and the like stored in the memory.