Image Extraction Apparatus Dynamic Threshold Noise Removal
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Solution Overview
Problem
Existing image processing technologies face challenges in effectively removing noise from extraction images, particularly when the difference in pixel values between background and extraction target images varies, leading to incomplete separation and complex user operations.
Innovation Solution
An image processing apparatus and method that allows users to selectively remove regions from extraction images based on operation input, featuring a display control unit that displays specifying frames and color designation marks, enabling easy identification and extraction of desired image regions with improved user operability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If separation between background and extraction target image is performed based on pixel value difference with user-set threshold, then noise removal capability is improved, but operation complexity increases and user operability deteriorates
Solution Approach 1:
The system automatically determines the threshold value for separating background and extraction target image without requiring user input. The determination unit calculates the threshold based on pixel value differences in the extraction target image, enabling the system to self-configurate and eliminating the need for users to manually set parameters, thus improving ease of operation while maintaining noise removal effectiveness
Solution Approach 2:
The system dynamically adjusts the threshold parameter based on the content and characteristics of the extraction target image. By changing the threshold value according to the specific image data rather than using a fixed or manually-set value, the system achieves optimal separation automatically, resolving the contradiction between effective noise removal and user-friendly operation
2Reliability
If threshold value is set to sufficiently remove noise from extraction target image, then noise removal effectiveness is improved, but operation complexity increases
Solution Approach 1:
The determination unit automatically calculates and sets the threshold value based on analyzing pixel value differences within the extraction target image itself. This self-service mechanism eliminates the need for users to manually adjust parameters or understand complex separation algorithms, reducing operational complexity while maintaining effective noise removal through automated optimization
3Productivity
If separation is performed based on fixed threshold, then processing speed is improved, but noise removal accuracy deteriorates when pixel value difference varies
Solution Approach 1:
The system transitions from using a fixed threshold to a dynamic threshold that automatically adapts to the specific characteristics of each extraction target image. The determination unit analyzes the pixel value distribution and content of the input image to calculate an appropriate threshold, enabling the system to maintain high processing speed while achieving accurate noise removal across varying image conditions through dynamic adjustment
Data Source
AI summary
A portable terminal includes an extraction unit and a display control unit. The extraction unit extracts a part of a display image displayed on a touch panel display, as an extraction image used as a compositing target image. The display control unit, in a case where a plurality of regions having different areas are included in the extraction image used as the compositing target image, removes at least one of the plurality of regions in order of area based on an operation amount of an operation input by a user.