Image Processing Apparatus Category Determination Segmentation
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Solution Overview
Problem
Existing image processing methods struggle to accurately determine the category of an original placed on a plate, leading to incorrect processing and storage format selection, especially when dealing with multiple originals of similar size or complex content, resulting in reduced accuracy and inefficiency.
Innovation Solution
An image processing method that determines whether a single original or multiple originals are present, extracts the relevant image components, and performs category-based processing, including binarization and noise reduction, to differentiate between document and photograph originals, enabling appropriate image processing and storage format conversion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image analysis is performed to achieve more appropriate image determination, then the accuracy of original category determination is improved, but the processing time becomes longer
Solution Approach 1:
The patent segments the determination process into two stages: first determining whether the image contains one or multiple originals using simple object count detection, then performing detailed category determination only on images containing a single original. This segmentation avoids applying complex analysis to all images, thus improving accuracy where needed while reducing overall processing time.
Solution Approach 2:
The patent applies partial action by performing detailed image analysis only on a subset of images that contain a single original, rather than analyzing all images with the same complexity. For images with multiple originals, a simpler determination approach is used, which reduces the total computational burden and processing time while maintaining appropriate accuracy for each case.
2Device complexity
If the category of an original is determined in accordance with the size of an object, then the determination process is simplified, but the determination accuracy is reduced because originals having the same size but having different categories exist
Solution Approach 1:
The patent implements a dynamic determination approach where the method used to categorize an original depends on the specific characteristics of the image being analyzed. If the image contains a single original, detailed analysis including brightness histogram and object shape is performed. If multiple originals are present, a different determination approach is used. This dynamic adaptation allows the system to maintain high accuracy while adjusting complexity based on the situation.
Solution Approach 2:
The patent changes the parameters used for determination based on the image content. For single originals, it uses a combination of parameters including brightness histogram, object shape, and size. For multiple originals, it primarily uses object count detection. This parameter adaptation allows accurate determination while avoiding unnecessary complexity in each specific case.
3Reliability
If appropriate processing is performed in accordance with the category of an original, then the image processing quality is improved, but the system complexity increases due to the need for accurate category determination
Solution Approach 1:
The patent segments the processing system into distinct modules: an object count detection module that quickly identifies whether an image contains one or multiple originals, and a category determination module that performs detailed analysis only when needed. This segmentation reduces overall system complexity by separating the always-executed simple detection from the conditionally-executed complex analysis.
Solution Approach 2:
The patent performs preliminary object count detection before performing detailed category determination. This preliminary action filters out images that don't require complex analysis (those with multiple originals), allowing the system to maintain high processing quality for relevant cases while reducing overall system complexity by avoiding unnecessary detailed analysis.
Data Source
AI summary
A method for processing an image obtained by reading an original plate on which at least one original is placed includes a determining step of determining whether the image is corresponding to one original or a plurality of originals placed on the original plate, an extracting step of extracting, from the image, one original image component corresponding to the one original or a plurality of original image components corresponding to the plurality of originals, and a processing step of performing image processing on the one or the plurality of extracted original image components, the image processing being different in accordance with the result of the determining step.