Digital Image Region Manipulation via Gesture and Edge Detection
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Solution Overview
Problem
Manual selection and manipulation of digital image regions for editing and broadcasting are time-consuming, especially in live environments, due to the need for precise identification and processing of image elements.
Innovation Solution
A method and apparatus that identify potential region borders based on edge content in digital images, allowing users to select and divide images into regions with pre-defined borders, and automatically launch processing tools using gesture data for efficient manipulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual image editing tools are used to identify and manipulate regions, then pixel accuracy can be achieved, but the process becomes time-consuming
Solution Approach 1:
The system performs preliminary actions by automatically detecting and proposing region borders based on image analysis before the user needs to select regions. The automatic border detection algorithm pre-processes the image to identify potential region boundaries, so when the user views the image, the regions are already prepared and ready for selection, eliminating the need for manual pixel-by-pixel boundary drawing.
Solution Approach 2:
The image editing system performs self-service through automatic region detection and border identification. The software autonomously analyzes the image content, detects edges and boundaries, and proposes region divisions without requiring manual intervention. This self-automating capability reduces dependency on manual operations while maintaining accurate region identification.
2Manufacturing precision
If multiple sequential operations (zoom, crop, select) are performed to manipulate image regions, then precise control is achieved, but productivity decreases
Solution Approach 1:
The system merges multiple sequential operations into a single unified gesture-based command. Instead of requiring separate zoom, crop, and select operations, the user can perform a single gesture that simultaneously defines the region boundary and triggers the desired manipulation operation. This consolidation maintains precision while dramatically improving productivity by reducing the number of discrete steps required.
Solution Approach 2:
The gesture-based interface provides universal control that can trigger multiple different manipulation operations (zoom, crop, pan, etc.) depending on the gesture type and context. A single gesture mechanism serves multiple functions, allowing the user to access various precision manipulation tools without needing separate controls for each operation, thereby improving both precision and productivity.
3Measurement precision
If traditional touch interfaces require separate steps for region selection and tool selection, then tool accuracy is maintained, but operation complexity increases
Solution Approach 1:
The system merges region selection and tool selection into a single integrated gesture. The gesture itself encodes both the region definition (through its spatial extent) and the tool selection (through its type or trajectory). This eliminates the need for separate menu navigation and tool selection steps, maintaining accurate tool selection while significantly improving ease of operation.
Solution Approach 2:
The interface performs self-service by automatically determining the appropriate tool based on the gesture characteristics and context. Instead of requiring the user to manually select a tool from a menu, the system analyzes the gesture and automatically applies the suitable manipulation operation, reducing operational complexity while maintaining precision through context-aware tool selection.
Data Source
AI summary
A method for dividing a digital image into regions comprises identifying potential region borders based on edge content in the digital image. The digital image is divided into regions based on user-selected ones of the potential region borders. A method of processing a region of a digital image comprises receiving gesture data for characterizing the region. A processing tool associated with the gesture data is automatically launched, and the region is processed using the processing tool.