Object Distinction via Pixel Correction and Mark Values
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Solution Overview
Problem
Existing image processing technologies face challenges in distinguishing between objects in an image when different resources are required for each object group, leading to low resource reusability and difficulty in recognizing attributes of objects at far locations.
Innovation Solution
A method where a same resource is configured for target objects in different object groups, with different mark values set for each group, allowing pixel correction to achieve distinct display attributes, thereby enabling object differentiation without the need for separate resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If different resources are configured for different object groups to enable object distinction, then object recognition accuracy is improved, but resource reusability deteriorates
Solution Approach 1:
The patent applies parameter changes by modifying the display attributes (color, brightness, saturation) of objects through pixel correction based on mark values. Instead of using different resources (models, textures) for different object groups, the system changes the display parameters of pixels belonging to objects with different mark values, achieving object distinction while reusing the same underlying resources.
Solution Approach 2:
The patent implements universality by making a single resource set serve multiple object groups simultaneously. The same 3D models, textures, and other resources are reused across different object groups, with differentiation achieved through post-processing pixel correction rather than dedicated resources for each group.
2Measurement precision
If multiple different resources are used for different object groups, then object differentiation is improved, but system complexity deteriorates
Solution Approach 1:
The patent merges the resource management approach by consolidating all object groups to use a common resource set. The differentiation function is merged into the rendering pipeline through a unified pixel correction process that handles all object groups simultaneously based on their mark values, rather than maintaining separate resource chains for each group.
3Measurement precision
If pixel correction is performed separately for each object group, then object distinction accuracy is improved, but processing time deteriorates
Solution Approach 1:
The patent applies segmentation by dividing the pixel correction process into separate handling for different object groups based on their mark values. Each object group receives targeted pixel correction with specific display attribute adjustments, allowing accurate distinction while organizing the processing in a structured manner that can be efficiently implemented in the rendering pipeline.
Data Source
AI summary
The present disclosure discloses a method and an apparatus for distinguishing objects. The method includes: obtaining a plurality of object groups displayed in an image, each object group including at least one target object, and a same resource being configured for target objects in different object groups; setting different mark values for the plurality of object groups, target objects in a same object group having a same mark value; and separately performing pixel correction on pixels of the target objects in each object group according to the mark value of each object group, pixels of the target objects having different mark values being corrected to have different display attributes.