Image Processing Apparatus Color Conversion for Object Extraction
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Solution Overview
Problem
Existing image processing technologies face challenges in accurately extracting object regions from images, particularly when the object and background colors are similar, leading to extraction noise, especially in white and black regions, and require extensive user registration of color information to achieve favorable results.
Innovation Solution
An image processing apparatus and method that involves acquiring images, designating extraction and non-extraction colors, deriving color conversion parameters, and performing color space conversion to improve object extraction accuracy by minimizing overextracted and unextracted regions through iterative adjustment and automatic computation of color conversion parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If color information is registered manually to improve extraction accuracy, then object extraction precision improves, but operation time and complexity increase
Solution Approach 1:
The system automatically computes color conversion parameters by analyzing the relationship between extraction colors and non-extraction colors, eliminating the need for manual registration and adjustment of color information. The processing unit autonomously determines the optimal color space transformation based on the provided color designations.
Solution Approach 2:
The system changes the color space parameters by deriving color conversion parameters that transform the color representation of pixels. This parameter transformation enables accurate object extraction without manual color registration, as the system adapts the color space to separate extraction colors from non-extraction colors automatically.
2Loss of time
If color conversion parameters are automatically derived, then operation time is reduced, but extraction accuracy may deteriorate
Solution Approach 1:
The system uses feedback from the color analysis process to refine the color conversion parameters. By examining the relationship between extraction colors and non-extraction colors, the processing unit iteratively adjusts and optimizes the conversion parameters to achieve both speed and accuracy in object extraction.
Solution Approach 2:
The system dynamically derives color conversion parameters based on the specific image content and color designations. This adaptive parameter change allows the system to maintain high extraction precision while operating automatically, as the parameters are optimized for each specific extraction task rather than using fixed pre-defined values.
3Measurement precision
If color space conversion is applied, then overextracted and unextracted regions are reduced, but processing complexity increases
Solution Approach 1:
The system applies color space conversion by transforming the color parameters of pixels using derived conversion parameters. This parameter transformation simplifies the extraction process by reorganizing color information in a way that naturally separates objects from background, reducing overextracted and unextracted regions without requiring complex multi-stage processing.
Data Source
AI summary
There is provided with an image processing apparatus for extracting an object region from an image. An image acquisition unit acquires an image. A designation acquisition unit acquires designation of one or more extraction colors that belong to the object region of the image and designation of one or more non-extraction colors that do not belong to the object region of the image. A derivation unit derives a color conversion parameter, based on the extraction color and the non-extraction color. A conversion unit converts a color of the image based on the color conversion parameter. An extraction unit extracts the object region from the image, based on the image and the extraction color after the conversion.