Graphical Element Alignment via Clustering Centroids
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Solution Overview
Problem
Users of graphics editing software face inefficiencies when manually aligning multiple graphical elements, particularly as the number of elements increases, requiring repetitive selection, alignment, and undoing processes to achieve visually appealing results.
Innovation Solution
A graphics editing tool employs a clustering algorithm to identify position coordinates of graphical elements, groups them into clusters based on validity scores, and aligns them automatically by setting their coordinates to centroid values, reducing manual effort and improving alignment precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual alignment process is used for multiple graphical elements, then flexibility in adjusting individual elements is maintained, but the time and effort required increases significantly as the number of elements grows
Solution Approach 1:
The patent segments the alignment process into two distinct modes: automatic alignment that handles bulk positioning of multiple elements simultaneously, and manual adjustment that allows individual element refinement. This segmentation resolves the contradiction by providing automated batch processing to reduce time while preserving manual control for flexibility when needed.
Solution Approach 2:
The system dynamically switches between automatic and manual alignment modes based on user needs. The automatic alignment provides rapid initial positioning, and users can then engage manual adjustment for specific elements requiring fine-tuning. This dynamic approach optimizes both time efficiency and operational flexibility throughout the design process.
2Manufacturing precision
If automatic clustering algorithm is used to align graphical elements, then alignment precision and efficiency improve, but the ability to handle custom alignment requirements decreases
Solution Approach 1:
The system incorporates feedback mechanisms where users can review automatically aligned elements and make adjustments. The automatic clustering provides high-precision initial alignment, and user feedback through manual adjustment refines the results for custom requirements. This feedback loop maintains both precision and adaptability.
Solution Approach 2:
The automatic clustering algorithm serves the alignment task independently with high precision, but the system also allows users to self-adjust individual elements when custom requirements arise. This self-service capability ensures that automated precision doesn't compromise user control for specialized needs.
3Ease of operation
If multiple graphical elements are aligned manually, then individual element control is maintained, but the complexity of the alignment process increases
Solution Approach 1:
The alignment process is segmented into automatic bulk alignment and individual manual adjustment phases. This reduces overall process complexity by handling the majority of alignment tasks automatically, while preserving individual element control for when users need to make specific adjustments.
4Reliability
If repetitive selection and alignment operations are performed, then alignment results can be achieved, but productivity decreases due to the iterative nature of the process
Solution Approach 1:
The system performs preliminary automatic alignment of all elements before any manual adjustment is needed. This preliminary action establishes high-quality initial positions for all elements simultaneously, eliminating the need for repetitive selection and alignment operations. Users can then make single-pass adjustments rather than iterative revisions, significantly improving productivity while maintaining result quality.
Data Source
AI summary
The present disclosure involves intelligent alignment of graphical elements for display within a graphical user interface. For instance, a graphics editing tool identifies position coordinates for a set of graphical elements and groups the position coordinates into one or more clusters. In some embodiments, the graphics editing tool selects the number of clusters for the clustering algorithm based on validity scores. For a given cluster, the graphics editing tool selects a centroid value of the cluster as an updated position value. The graphics editing tool aligns a subset of the graphical elements associated with the cluster by moving each graphical element to the updated position value. For instance, the graphic editing tool can change a horizontal coordinate value or a vertical component value for each graphical element to the centroid value. The graphics editing tool causes a display device to display the aligned graphical elements.