Image Border Snapping via Edge Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image editing tools face challenges in defining borders quickly and accurately, allowing for natural transitions from foreground to background, and correcting mistakes during the border definition process, especially when dealing with complex images like those containing multiple colors or textures.
Innovation Solution
An image-editing method that identifies edges in an image, snaps a border to these edges as the cursor moves, and generates a tunnel for transition, allowing for dynamic border definition, deletion of border segments, and modification of tunnel width and shape for accurate foreground-to-background transitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a user draws a border by manually moving the cursor to define the selection, then the border can be precisely placed, but the process becomes very time-consuming and difficult
Solution Approach 1:
The system automatically identifies edges and snaps the border to them, allowing the border definition process to serve itself by utilizing the image's inherent edge information rather than requiring manual pixel-by-pixel cursor movement
Solution Approach 2:
The patent replaces the mechanical cursor movement system with an automated edge detection and snapping system that uses image processing algorithms to automatically position the border along edge pixels
2Measurement precision
If a user must complete the entire border definition without mistakes, then the selection accuracy can be maintained, but the process becomes frustrating and requires multiple attempts
Solution Approach 1:
The system pre-identifies all edges in the image before the user defines the border, so that when the user moves the cursor, the border automatically snaps to the nearest edge, eliminating the need for precise manual positioning and allowing easy correction of mistakes
Solution Approach 2:
The border definition process provides continuous feedback by automatically snapping to identified edges, allowing users to see the border adjust in real-time and easily correct mistakes by simply moving the cursor to the desired location
3Ease of operation
If a simple softening effect is applied to the selection edge, then the transition from foreground to background is smoother, but the transition does not account for the actual nature of the border
Solution Approach 1:
The patent applies different processing to different parts of the border by identifying edge pixels and creating a transition region that is specifically tailored to the local characteristics of each border segment, rather than applying a uniform softening effect
Data Source
AI summary
Some embodiments provide a method for selecting a portion of an image. The method identifies edges in the image. The method defines a border about the portion of the image by using the identified edges. The method represents the border as a deformable curve. In some embodiments, defining the border includes detecting a cursor moving over the image and defining the border along identified edges in the vicinity of the cursor. In some embodiments, the method searches for edges in the vicinity of the cursor and snaps the border to the edges. Identifying the edges of the image includes performing an edge detection algorithm in some embodiments. Identifying the edges further includes performing a de-noise algorithm in some embodiments. In some embodiments, the parametrizable curve is a bezier spline.