Small Vector Image Generation via Contrast Thresholding
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Solution Overview
Problem
Existing methods for generating small vector images from analog imagery captured by computing devices are inefficient in separating the imagery from its background, leading to suboptimal image editing and composition capabilities.
Innovation Solution
A computing device executes instructions to define a marked area, separate the analog imagery from the background using a contrast threshold value, and generate a small vector image with a transparent background, allowing for customizable and layered image creation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing methods are used to generate small vector images from analog imagery, then the image generation process can be completed, but the separation of imagery from background is inefficient and suboptimal
Solution Approach 1:
The patent transforms the input image to grayscale and applies gamma correction to adjust the luminance distribution, making the contrast thresholding operation more effective. These parameter transformations prepare the image data for efficient and accurate background separation.
Solution Approach 2:
The patent replaces manual or complex mechanical image separation processes with an automated computational approach using contrast thresholding. This algorithmic method efficiently separates foreground imagery from background by comparing pixel luminance values against a calculated threshold.
2Adaptability or versatility
If analog imagery is captured and processed, then custom vector images can be created, but the background separation leads to suboptimal editing and composition capabilities
Solution Approach 1:
The patent applies gamma correction with a specific gamma value (typically 2.2 for sRGB) to transform the luminance values, enhancing the separation between foreground and background. This parameter transformation improves the accuracy of subsequent thresholding operations, enabling better editing versatility.
Solution Approach 2:
The patent introduces an intermediate processing stage that converts the captured image to grayscale and applies luminance transformations before final vectorization. This intermediary processing step serves as a bridge between raw capture and final vector output, improving overall separation quality.
3Adaptability or versatility
If contrast thresholding is applied to separate imagery from background, then transparent background generation is enabled, but additional processing steps are required
Solution Approach 1:
The patent combines multiple operations—grayscale conversion, gamma correction, and contrast thresholding—into a unified processing pipeline. This merging of operations achieves transparent background generation while managing workflow complexity through integrated processing steps.
Solution Approach 2:
The system automatically calculates the contrast threshold based on the image's luminance distribution and applies the separation without requiring manual intervention. This self-service approach enables transparent background capability while minimizing the complexity of user interaction.
Data Source
AI summary
In some examples, a computing device can define a marked area of an image of analog imagery captured by the computing device, separate the analog imagery of the image from a background of the image, and generate a small vector image that includes the analog imagery of the image.