Object Position Detection via 1-D Distance-Axis Signal Conversion
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Solution Overview
Problem
Existing blind-spot detection systems in vehicles face limitations such as smaller view fields, high costs, and difficulty in detecting objects in large areas, with current image processing technologies being resource-intensive and influenced by environmental illumination, and requiring multiple algorithms for day and night conditions.
Innovation Solution
The system converts 2-D image data into 1-D distance-axis signal information using a complexity estimation method and performs numerical differentiation to determine object presence and approaching status, allowing for accurate detection without radar and with reduced computational requirements, applicable to existing imaging systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If distance detection radar is used to detect object position, then detection accuracy is improved, but device cost and complexity increase
Solution Approach 1:
The patent replaces complex radar systems (electromagnetic/ultrasonic) with a simpler image processing system that uses digital signal processing of camera images. The image processing unit analyzes image data to detect object positions, distances, and approaching status without requiring radar hardware, thereby reducing system complexity and cost while maintaining detection accuracy
Solution Approach 2:
The patent creates a digital representation (1-D distance-axis signal) of the physical distance information from image data. By converting visual information into distance-axis signals and analyzing their differential values, the system replicates radar's distance detection capability using software-based image processing instead of hardware-based radar
2Area of stationary object
If multiple vehicular radars are mounted to reduce blind spots, then detection coverage is improved, but device cost increases
Solution Approach 1:
The patent transitions from multiple discrete radar units covering different angular regions to a single wide-field image capture approach. By capturing the entire field of view in one image and processing it to extract distance information along the detection direction, the system achieves comprehensive coverage without multiplying hardware components
3Measurement precision
If conventional image processing algorithms are used to detect objects, then object detection is achieved, but computational resources are heavily consumed
Solution Approach 1:
The patent extracts only the essential information needed for detection by converting 2-D image data into 1-D distance-axis signal information. This extraction process removes redundant spatial details while preserving distance and motion information, significantly reducing the computational load for subsequent differential value calculations
Solution Approach 2:
The patent changes the parameter representation from 2-D spatial coordinates to 1-D distance-axis signals. This parameter transformation simplifies the data structure and enables more efficient computational algorithms for detecting object positions and motion status, reducing energy consumption while maintaining detection accuracy
4Measurement precision
If conventional image processing is used to detect objects, then object position can be determined, but detection is influenced by environmental illumination
Solution Approach 1:
The patent transforms the detection parameter from direct image intensity analysis to differential value analysis of distance-axis signals. By computing differences between adjacent time points and differential values, the system detects motion-induced changes that are independent of absolute illumination levels, making detection robust against environmental lighting variations
Data Source
AI summary
The present invention discloses a fast object position detection device and a method thereof, particularly to a detection device and a method thereof which can directly apply to various image systems. The device of the present invention mainly comprises an image capturing system that captures images within the regions defined by the user, and an image processing unit determining the position of an object and obtaining related information. In the method of the present invention, a captured image is converted into 1-D distance-axis signal information; a differential value of the 1-D distance-axis signal information is used to determine a position of an object; and a difference of the 1-D distance-axis signal information of at least two adjacent time points is used to determine an approaching status of an object.