Polygonal Boundary Definition for Image Objects
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Solution Overview
Problem
Current methods for identifying image object boundaries in digital images are time-consuming and computationally inefficient, limiting the use of 2D image element hot linking in various applications.
Innovation Solution
A system and method that starts with a known point in an image object, identifies adjacent pixels sharing a characteristic like color, builds a list of boundary pixels, and recursively adds contiguous region boundaries to define a polygon, with optional reduction of the list to simplify the boundary representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual boundary identification is used, then boundary definition accuracy is achieved, but time consumption increases significantly
Solution Approach 1:
The patent replaces manual mechanical boundary identification with an automated computer-based system that uses image processing algorithms to automatically detect and define object boundaries, eliminating the need for manual pixel-by-pixel analysis while maintaining accuracy
Solution Approach 2:
The system enables self-service boundary identification by automatically analyzing image data, detecting edges, and generating boundary definitions without human intervention, allowing the computer to perform the task independently and efficiently
2Measurement precision
If complex algorithms are used for boundary identification, then boundary accuracy is improved, but computational efficiency deteriorates
Solution Approach 1:
The patent segments the boundary identification process into distinct computational stages including edge detection, boundary tracing, and polygon approximation, allowing each stage to be optimized independently and processed efficiently rather than using a single complex algorithm
Solution Approach 2:
The system uses simplified boundary representation models that approximate complex boundaries with polygons of limited precision, sacrificing minimal accuracy for significant gains in computational speed and ease of processing
3Measurement precision
If detailed boundary pixel lists are maintained, then boundary precision is preserved, but data storage and processing requirements increase
Solution Approach 1:
The patent extracts only the essential boundary-defining pixels from the complete set of boundary pixels, removing redundant intermediate pixels that do not contribute to the final boundary definition, thereby reducing data storage requirements while preserving boundary accuracy
Solution Approach 2:
The system dynamically adjusts the level of boundary detail based on application requirements, allowing the boundary representation to be simplified or refined as needed rather than maintaining fixed high-detail pixel lists for all cases
Data Source
AI summary
Image objects within two-dimensional images are identified by locating boundary points that describe line segments that define a polygon outlining each object. Processing follows lines of pixels between boundary points to determine whether additional pixels are a part of the same image object by reference to a discriminator, such as color. Boundary points are thus identified for contiguous pixels and contiguous lines. Arm-like regions are identified by recursive analysis in a similar manner. The resulting boundary point list may serve to identify the image object, such as for labeling or tagging in web-based manuals, catalogs, and so forth.