Image Processing Apparatus Region Class Identification
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Solution Overview
Problem
Existing image processing techniques struggle to precisely identify the class of each region in an image due to reliance on feature quantities alone, without effectively utilizing additional information available during image capture.
Innovation Solution
An image processing apparatus that acquires image capturing information and estimates the distribution of class existence at each region, using this information along with image data to identify classes through an estimation unit and identification unit, incorporating techniques like existence probability distribution estimation and classifier-based identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only feature quantities from image data are used for class identification, then the processing is simple and fast, but the class identification precision is insufficient
Solution Approach 1:
The patent combines multiple types of data (image data and non-image data from sensors) to create a comprehensive feature set for class identification. The estimation unit processes both image features and non-image features together, merging their information to achieve higher identification precision without treating them as separate independent processes.
Solution Approach 2:
The estimation unit serves multiple functions by processing both image data and non-image data through a unified framework. It estimates the degree of existence for multiple classes simultaneously using combined features, making the system versatile and efficient rather than requiring separate specialized processors for different data types.
2Measurement precision
If additional image capturing information is integrated for region segmentation, then the class identification accuracy improves, but the information processing complexity increases
Solution Approach 1:
The system performs preliminary estimation of the degree of existence for each class in each region before final identification. By pre-processing and estimating class probabilities using combined image and non-image data, the system prepares region-specific class distributions in advance, reducing the information processing load during final identification while maintaining high accuracy.
Solution Approach 2:
The patent applies different processing strategies to different regions based on their specific characteristics. The estimation unit analyzes each region individually to determine the degree of existence of classes, allowing the system to focus computational resources on regions that require more attention while using simpler processing for well-defined regions, thus managing information processing load effectively.
Data Source
AI summary
In order to precisely identify a class relating to classification of an object at each of regions of an image, an image processing apparatus includes an acquisition unit configured to acquire image capturing information when the object has been captured, an estimation unit configured to estimate distribution relating to a degree of existence of each class which indicates classification of the object at each of predetermined regions of a captured image of the object based on the image capturing information acquired by the acquisition unit, and an identification unit configured to identify the class at each of the regions based on distribution information indicating the distribution estimated by the estimation unit and image information relating to the captured image.