Electromagnetic Wave Image Processing for Low-Data Object Detection
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Solution Overview
Problem
Existing object detection techniques using electromagnetic waves face challenges in reducing data signal amounts while maintaining estimation accuracy, leading to reduced image sharpness and difficulty in manual labeling operations.
Innovation Solution
A processing apparatus and method that generates label determination and learning images using partial signals of reflection waves, associates these with labels to create training data, and employs machine learning to develop an estimation model for accurate object detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the amount of electromagnetic wave signal data is reduced to minimize processing load and device complexity, then processing load and device complexity are reduced, but image sharpness deteriorates making manual labeling difficult
Solution Approach 1:
The patent segments the signal processing into two distinct paths: a label determination image generation path using full signal data for high sharpness, and a learning image generation path using partial signal data for reduced complexity. This segmentation allows each path to optimize for its specific purpose without compromising the other.
Solution Approach 2:
The patent applies local quality by using different signal data quantities in different processing stages and paths. Full signal data is used where high quality is needed (label determination), while partial signal data is used where reduced complexity is acceptable (learning image generation for training models).
2Weight of stationary object
If the amount of electromagnetic wave signal data is reduced to miniaturize sensor devices and lower costs, then device size and cost are reduced, but image sharpness deteriorates making manual labeling difficult
Solution Approach 1:
The patent segments the image generation process into two independent paths that can use different data quantities. The label determination path uses full data for sharp images, while the learning image path uses reduced data for model training, allowing device miniaturization without compromising labeling capability.
Solution Approach 2:
The patent creates a copy of the signal processing system that operates with reduced data quantity. This copied path (learning image generation) allows device miniaturization and cost reduction while the original path (label determination) maintains full capability for sharp image generation and manual labeling.
3Loss of time
If the amount of electromagnetic wave signal data is reduced to shorten irradiation time and suppress motion blur, then time resolution is improved, but image sharpness deteriorates making manual labeling difficult
Solution Approach 1:
The patent segments the signal processing into parallel paths: one path uses full signal data for high sharpness when time is not critical, while the other path uses partial signal data to achieve faster processing with acceptable sharpness for model training purposes.
Solution Approach 2:
The patent applies different quality levels locally to different processing paths. The label determination path maintains high quality for critical applications, while the learning image path accepts reduced quality in exchange for faster processing speed and reduced motion blur.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Reduces processing load, miniaturizes sensor devices, and lowers costs by minimizing data transmission while maintaining estimation accuracy and enabling effective labeling operations.
Implementation Method 1
an electromagnetic wave transmission/reception means for irradiating an electromagnetic wave from a transmission antenna, and receiving a reflection wave by a reception antenna
Implementation Method 2
receiving a reflection wave by a reception antenna
Data Source
AI summary
The present invention provides a processing apparatus (10) including an electromagnetic wave transmission/reception unit (11) that irradiates an electromagnetic wave from a transmission antenna, and receives a reflection wave by a reception antenna; a label determination image generation unit (12) that generates a label determination image, based on a signal of the received reflection wave; a learning image generation unit (13) that generates a learning image, based on a signal being a part of a signal of the receive reflection wave, and less than a signal to be used in generation of the label determination image; a label determination unit (14) that determines a label, based on the label determination image; and a training data generation unit (15) that generates training data in which the learning image and the label are associated, and causing a training data storage unit (16) to store the generated training data.