Strip-Based Auto-Color Detection in Software Image Paths
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Solution Overview
Problem
Software-based image processing in multifunction devices is inefficient due to the current implementation of auto-color features, which does not optimize processing time and quality, particularly in converting images between color spaces, leading to suboptimal performance compared to hardware-based systems.
Innovation Solution
Implementing a strip-based color detection and processing method using image signal processors to split input images into strips, determining the presence of color data within each strip, and generating either monochrome or color renderings accordingly, with tetrahedral interpolation for color strips after declaring a page as color, thereby reducing unnecessary processing and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If both CMYK and monochrome images are simultaneously generated during neutral page detection in software-based image path, then the auto-color feature can be implemented, but the processing time and computational load increase significantly
Solution Approach 1:
The patent divides the image processing into segments by splitting the input image into multiple strips. Each strip is processed independently for color detection, allowing parallel processing and early termination when color is detected in any strip. This segmentation reduces the overall processing time compared to processing the entire image at once while maintaining the auto-color detection capability.
Solution Approach 2:
The patent performs preliminary color detection on individual strips before committing to full color or monochrome processing of the entire page. By detecting color content in advance on a strip-by-strip basis, the system can make early decisions about processing mode, avoiding unnecessary full-color processing of entire pages that could be monochrome, thus reducing computational load and processing time.
2Stability of the object's composition
If monochrome rendering is continued for all strips even after color is detected, then consistent processing is maintained, but unnecessary computations increase processing time
Solution Approach 1:
The patent introduces dynamic adjustment to the processing pipeline by allowing the processing mode to change based on detected content. When color is detected in a strip, the system dynamically switches from generating both CMYK and monochrome images to generating only CMYK images for subsequent strips. This dynamic adaptation maintains processing consistency within each mode while improving overall efficiency by avoiding unnecessary monochrome rendering after color detection.
Solution Approach 2:
The patent applies different processing quality levels to different regions of the image based on local color detection results. Strips detected as containing color receive full CMYK processing, while subsequent strips on pages where color was detected skip monochrome rendering. This local quality adjustment ensures appropriate processing for each region while reducing redundant computations.
3Ease of manufacture
If software-based image path is used instead of hardware-based, then cost and flexibility improve, but performance and processing speed deteriorate
Solution Approach 1:
The patent implements segmentation of the image into strips that can be processed in parallel, enabling software-based processing to achieve hardware-like speeds. By dividing the workload into independent strip-level tasks, the system can utilize multi-core processors and optimize memory access patterns, closing the performance gap with hardware-based systems while maintaining the cost and flexibility advantages of software.
Solution Approach 2:
The patent changes processing parameters dynamically based on detected image characteristics. By adjusting the level of processing (full color vs. monochrome) based on actual content analysis, the system optimizes computational resource usage. This parameter adaptation allows software-based processing to achieve high performance on color-rich images while consuming fewer resources on monochrome content, matching hardware system efficiency.
Data Source
AI summary
A method and system for an auto-color detection and color transformation is provided including with at least one image signal processor, splitting an input image into a plurality of strips on a page. Each strip is composed of a plurality of pixels. The presence of color data within a strip is determined. Based on a determination that no color data is present within the strip both a monochrome rendering and a simple color rendering of this neutral strip are generated. Based on a determination that color data is present within a strip, the entire page is declared a color page and either one of a simple color rendering (via 1D look up tables) or a complex color rendering (via tetrahedral interpolation) of the strip is generated. Thereafter, only color renderings of subsequent strips is performed for the corresponding page.