Lexical Classifier Image Element Selection
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Solution Overview
Problem
Conventional methods for selecting a subset of image pixels based on color are cumbersome, as users find it difficult to relate tolerance values to selected pixel colors and are limited to regular geometric shapes in color space, making accurate selection challenging.
Innovation Solution
A method using lexical classifiers to characterize visual attributes of image elements, allowing selection based on a reference classifier, enabling intuitive selection of image elements by associating each element with a color name or modifier, and comparing these to a reference for accurate subset creation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional RGB tolerance-based selection is used, then the selection process is simple to implement, but the user cannot accurately control which pixel colors are selected and is limited to regular geometric shapes in color space
Solution Approach 1:
The patent transforms the color selection parameter from numerical RGB tolerance values to lexical color descriptors (color names and modifiers). This parameter change enables users to specify color regions using natural language terms like 'dark red' or 'light blue' instead of adjusting numerical tolerances, thereby improving both selection accuracy and user control over the selected pixel colors
Solution Approach 2:
The patent introduces lexical classifiers as an intermediary between the user's color perception and the numerical color space. The lexical classifiers map human-readable color descriptions to specific regions in the color space, allowing users to select irregular color regions without directly manipulating numerical tolerances or understanding color space geometry
2Ease of operation
If lexical classifiers are used to characterize visual attributes, then the selection becomes more intuitive and accurate, but the system complexity increases due to the need for classifier databases and comparison logic
Solution Approach 1:
The patent performs preliminary classification of pixel colors into lexical categories before the actual selection operation. By pre-computing and storing lexical classifiers for all pixels in the image, the system prepares the data in a form that enables intuitive user interaction during selection, while the classification work is done in advance
Solution Approach 2:
The patent creates a lexical representation copy of the color attributes for each pixel. Instead of working directly with complex numerical color values and tolerance calculations, the system uses simplified lexical classifier copies that preserve the essential color information in a more manageable and intuitive form
Data Source
AI summary
A method and system for selecting image elements, such as image pixels or vectors, of a digital image provide a set of lexical classifiers, such as a set of color names, which characterize a visual attribute of the image elements such as color. A lexical classifier is assigned to each image element, e.g. by a transform between the image element color values under the original numerical color encoding model of the image and the set of lexical classifiers. A reference lexical classifier is selected, e.g. by selecting an image element and determining its associated lexical classifier, and the image elements are then selected if their lexical classifier corresponds to the reference lexical classifier. The selected image elements may then be acted on as a group.