Trolley tracking obstacle avoidance identification method based on ternary processing

Abstract

The invention discloses a trolley tracking obstacle avoidance identification method based on ternary processing, which comprises the following steps that a camera collects image signal data and sends the image signal data to a processor; the processor extracts brightness characteristics from the image signal data and performs black and white processing on the image signal data; the processor determines an image pixel point threshold value according to the brightness characteristics and performs ternary processing on the black-and-white image signal data; the processor determines a primary path road condition according to the ternary image signal data and generates primary path road condition image signal data; the processor carries out particle noise removal processing on the primary path road condition image signal data and determines a secondary path road condition, and the processor controls the trolley to act according to the secondary path road condition data; the precision that the processor controls the trolley to act is greatly improved, the cost is reduced, and system components are simplified.

Description

technical field [0001] The invention relates to the technical field of intelligent identification information, in particular to a ternary-based identification method for tracking and avoiding obstacles of a car. Background technique [0002] At present, artificial intelligence algorithms rely on many sensors, such as cameras, infrared light sensors, ultrasonic sensors, and radars. The increase in the number of sensors increases the cost on the one hand, and on the other hand, multiple sensors occupy the computing resources of the processor, resulting in an increase in the computing power of the processor. At the same time, there is also a problem of mutual coordination and cooperation between multiple sensors. If the cooperation is not good, it will cause system errors. The traditional camera recognition ribbon road can only recognize the boundary of the road. For obstacles on the road, additional sensors such as ultrasonic sensors are required to measure obstacles. Conte...

AI Technical Summary

Problems solved by technology

The increase in the number of sensors increases the cost on the one hand, and on the other hand, multiple sensors occupy the computing resources of the processor, resulting in an increase in the computing power of the processor.

At the same time, there is also a problem of mutual coordination and cooperation between multiple sensors. If the cooperation is not good, it will cause system errors.

The traditional camera recognition ribbon road can only recognize the boundary of the road. For obstacles on the road, additional sensors such as ultrasonic sensors and other obstacles are required.

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