Image Binarization with Shadow Component Correction
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Solution Overview
Problem
Existing binarization processing techniques fail to accurately handle shadow components and illumination reflections in image data, leading to incorrect conversion of image areas, such as converting a blank sheet's area into black and inaccurately processing the outer peripheral area of illumination.
Innovation Solution
An information processing apparatus that acquires an image of a shadow component, specifies areas with higher luminance, corrects the image by reducing the luminance of the outer peripheral area, and generates a binary image using a threshold map, effectively addressing shadow and illumination reflections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If binarization processing is performed using a single threshold for each pixel, then the processing is simple and fast, but shadow components and illumination reflections cause incorrect conversion of image areas
Solution Approach 1:
The patent segments the image processing into multiple stages: first acquiring shadow component information, then specifying high-luminance areas representing illumination reflections, correcting the image by reducing luminance in outer peripheral areas, and finally performing binarization. This segmentation allows each stage to address specific issues independently, improving overall accuracy without sacrificing processing efficiency.
Solution Approach 2:
The patent performs preliminary actions before binarization by first acquiring shadow component images, specifying illumination reflection areas, and correcting the multi-valued image. These preliminary steps prepare the image data by removing shadow and reflection effects, ensuring that the subsequent binarization operates on corrected data, thereby improving accuracy while maintaining a streamlined process.
2Device complexity
If shadow components are not taken into consideration in binarization processing, then the processing is simpler, but areas with shadow components are incorrectly converted into black
Solution Approach 1:
The patent extracts shadow component information from the image data before performing binarization. By separating and identifying shadow areas, the system can exclude them from the binarization decision process, preventing incorrect conversion of shadowed regions while maintaining processing efficiency through targeted correction.
Solution Approach 2:
The patent introduces an intermediary correction step between image acquisition and binarization. This intermediary process uses shadow component information and illumination reflection detection to adjust the multi-valued image, creating a corrected intermediate representation that accurately reflects the true image content without shadow or reflection artifacts, thereby improving binarization accuracy.
3Productivity
If illumination reflection is present in image data, then the image capturing is faster, but binarization processing on outer peripheral area cannot be accurately performed
Solution Approach 1:
The patent implements a feedback mechanism by detecting illumination reflection areas in the captured image and using this information to guide the correction process. The system identifies high-luminance areas representing reflections, applies targeted luminance reduction in outer peripheral regions, and then performs binarization on the corrected image, thereby maintaining capturing speed while improving peripheral area accuracy through adaptive correction.
Data Source
AI summary
An aspect of the present disclosure includes acquiring an image representing a shadow component in an image capturing environment, the shadow component being reflected in a multi-valued image obtained by capturing an image of a subject; specifying an area having a luminance greater than a predetermined luminance value, the area being included in the image representing the shadow component acquired in the acquiring; correcting the image in such a manner that a luminance of an outer peripheral area of the specified area deceases; and generating a binary image by performing binarization processing on a pixel value of a pixel of interest in the multi-valued image based on a pixel value at the same coordinates as those of the pixel of interest in the corrected image.