Hand-drawn Arrow Detection via Tip Pixel Estimation and Edge Refinement
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Solution Overview
Problem
Computer recognition of hand-drawn arrows in images is challenging due to the variety of arrowhead styles, making it difficult to convert such images into an electronically editable format.
Innovation Solution
A method and system that identify candidate arrows by determining their direction, estimating the tip pixel, and refining arrowhead edges, which are then matched against arrow descriptions to accurately recognize and replace hand-drawn arrows with graphic representations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If computer recognition algorithms are applied to identify hand-drawn arrows in images, then the conversion to editable format is enabled, but the recognition accuracy deteriorates due to the variety of arrowhead styles
Solution Approach 1:
The patent segments the arrow recognition process into distinct components: identifying the shaft, locating the tip pixel, detecting arrowhead edges, and classifying arrowhead styles. This segmentation allows each component to be processed independently with specialized algorithms, improving overall recognition accuracy despite style variations.
Solution Approach 2:
The patent changes parameters such as direction angle, tip pixel coordinates, and edge characteristics to classify different arrowhead styles. By transforming the recognition problem into parameter space, the system can accurately distinguish between various arrowhead styles despite their visual diversity.
2Productivity
If simple shape recognition methods are used, then processing speed is improved, but the ability to accurately recognize hand-drawn arrows with varied arrowhead styles deteriorates
Solution Approach 1:
The patent performs preliminary actions by first identifying the shaft and determining the direction before focusing on arrowhead detection. This preliminary structuring of the problem allows subsequent steps to operate more efficiently and accurately, maintaining both speed and reliability.
Solution Approach 2:
The patent applies local quality by using different processing strategies for different parts of the arrow: the shaft is processed using line detection, while the arrowhead is processed using edge detection and style classification. This localized approach optimizes both speed and accuracy for each component.
3Measurement precision
If detailed analysis of arrowhead edges is performed to improve recognition accuracy, then the precision of arrow identification is improved, but the computational complexity and processing time increase
Solution Approach 1:
The patent extracts only the essential features needed for arrowhead style classification: the tip pixel location and the edges radiating from it. By extracting only these critical elements rather than analyzing the entire arrow, the system achieves high precision with manageable complexity.
Solution Approach 2:
The patent performs partial action by focusing computational resources only on the arrowhead region after the shaft and tip are identified. This selective analysis provides sufficient precision for recognition without the excessive computational cost of analyzing the entire image in detail.
Data Source
AI summary
A method for processing an image with a processor, including: identifying, within an image, a candidate arrow including a long path adjacent to a plurality of short paths; determining a direction of the candidate arrow based on the long path; estimating a tip pixel within the plurality of short paths based on the direction of the candidate arrow; determining, for the candidate arrow, a plurality of arrowhead edges in the plurality of short paths based on the tip pixel; and generating, for the candidate arrow, a plurality of refined arrowhead edges based on the plurality of arrowhead edges, the direction, and the tip pixel.