Vehicle Camera Recognition Logic Diagnostic Apparatus
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current vehicle systems that use camera sensors to recognize targets in images may fail to accurately control vehicle devices, leading to safety risks due to recognition errors, necessitating a robust diagnostic method to ensure correct operation.
Innovation Solution
An apparatus and method that utilize an image frame with reference characteristic points to determine the normal operation of recognition logic by comparing calculated coordinates of recognized points with pre-defined coordinates, embedded in the system to function regardless of external conditions, and adjust processing based on processor load rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If recognition logic is used to identify targets in vehicle images, then vehicle control automation is improved, but recognition errors may occur leading to safety risks
Solution Approach 1:
A reference image frame with known characteristic points is introduced as an intermediary standard to verify recognition logic operation. The diagnosis apparatus compares recognized characteristic points against these reference points to determine whether the recognition logic is functioning normally, providing an objective reference that mediates between the automated recognition system and safety verification requirements.
Solution Approach 2:
The system performs self-diagnosis by using its own recognition logic to process a reference image frame and compare results against predetermined characteristic points. This self-verification mechanism allows the system to autonomously monitor its own operational status without requiring external intervention, ensuring continuous reliability checking.
2Measurement precision
If environmental factors such as weather are considered in target recognition, then recognition accuracy is improved, but system complexity increases
Solution Approach 1:
The diagnostic function extracts and isolates the recognition logic verification from the main target recognition process. By separating the self-diagnosis mechanism into an independent subsystem that uses reference image frames, the system can verify recognition accuracy without being affected by variable environmental conditions during normal operation, thus maintaining simplicity while ensuring precision.
3Reliability
If comprehensive diagnostic checks are performed continuously, then system reliability is improved, but processing time and computational load increase
Solution Approach 1:
The diagnosis apparatus performs recognition logic verification at predetermined time intervals by periodically inputting reference image frames. This periodic diagnostic approach balances reliability monitoring with processing efficiency, ensuring the system checks its own operation status regularly without continuously consuming computational resources or processing time.
Data Source
AI summary
An apparatus for diagnosing a failure of recognition logic, which recognizes a target in an image obtained by a vehicle, including: an image frame including coordinates of a reference characteristic point of a set target; a camera sensor photographing a front side of the vehicle and outputting an image of the front side; a recognition logic unit calculating coordinates of a characteristic point in the image frame and outputting coordinates of a recognized characteristic point; an image frame compulsory input unit applying the image frame to the recognition logic unit at a predetermined period instead of the image of the front side of the vehicle; and a normal operation determining unit determining whether the recognition logic unit is normally operated according to whether the coordinates of the reference characteristic point are matched with the coordinates of the recognized characteristic point during the compulsory input of the image frame.