Automated Trap Direction Determination by Luminance Comparison
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Solution Overview
Problem
Conventional trapping processes in printing and plate making often generate trap graphics in undesirable directions between images or between images and color objects, leading to reduced image quality and increased user effort for manual correction.
Innovation Solution
An image processing apparatus and method that automatically determine the trap direction by extracting sample coordinate points and acquiring color values along the boundary between overlapping objects, calculating luminance levels, and generating trap graphics on the object with a lower brightness level, thereby eliminating the need for manual user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If trap graphics are generated automatically between images or between images and color objects using conventional trap rules, then the trapping process can be performed without manual intervention, but the trap graphics are generated in undesirable directions leading to reduced image quality
Solution Approach 1:
The invention changes the parameter used for determining trap direction from fixed trap rules to dynamic luminance level comparison. By calculating the average luminance level of each object at sample coordinate points along the boundary and comparing these values, the system automatically determines the correct trap direction based on actual image content rather than predetermined rules, thereby improving image quality while maintaining automation.
2Manufacturing precision
If trap graphics are generated on darker-colored objects to make them less noticeable, then image quality is preserved, but this approach cannot be applied consistently when both objects are images with varying luminance levels from pixel to pixel
Solution Approach 1:
The invention applies local quality by calculating the average luminance level at specific sample coordinate points along the boundary between objects, rather than using a single fixed luminance value for the entire object. This allows the system to determine trap direction based on the local luminance characteristics at the boundary region, making the method adaptable to both color objects with uniform luminance and image objects with varying pixel luminance levels.
3Ease of manufacture
If conventional trap rules are used to determine trap direction between images, then the process is simple to implement, but manual correction is required when trap graphics are generated in undesirable directions
Solution Approach 1:
The invention implements self-service by enabling the trapping system to automatically determine the correct trap direction through luminance level comparison without requiring user intervention. The system calculates average luminance levels at sample coordinate points, compares them to identify the darker object, and automatically places trap graphics on the appropriate object, eliminating the need for manual correction while maintaining process simplicity.
Data Source
Figure 1
Figure 2A~2C
Figure 3
AI summary
A neighboring vector, which is a boundary portion between two overlapping objects, is extracted (S160). To calculate luminance levels of the objects on both sides of the neighboring vector, a predetermined number of coordinate points (sample points) in the vicinity of the neighboring vector are extracted at least from the image side (S170). A rendering process is performed on an area including all the extracted sample points to acquire color values at the sample points (S180). The luminance level of the image is calculated based on the acquired color values, and the luminance levels of the objects on both sides of the neighboring vector are compared to each other to determine the position (direction) in which to generate a trap graphic (S190).