Fuzzy self-adaptive control system for parameters of visual sensor

Abstract

The invention provides a fuzzy self-adaptive control system for parameters of a visual sensor. The system is characterized in that a signal output end of a detection device is connected with a signal input end of an input interface; a signal output end of the input interface is connected with a signal input end of a fuzzy controller; a signal output end of the fuzzy controller is connected with asignal input end of an output interface; a signal output end of the output interface is connected with a signal input end of an execution mechanism; a signal output end of the execution mechanism is connected with a signal input end of a control object; and a signal output end of the control object is connected with a signal input end of the control object. The system has the advantages that a fuzzy self-adaptive control algorithm does not adopt human eye observation, system time and other unreliable factors; closed loop control on parameters of the visual sensor is realized; input parametersare fuzzified, set parameters of the video sensor have high setting speed through the fuzzy controller; and the parameters are regulated and set in real time. The input parameter is calculated through the fuzzy controller, so that the best image quality and effect can be acquired for the sensor.

Description

technical field

[0001] The invention relates to a fuzzy self-adaptive control system of visual sensor parameters, which is suitable for technical fields such as safety monitoring, intelligent transportation, high-definition video conferencing, high-definition medical video diagnosis, and distance education. Background technique

[0002] At present, in ordinary surveillance cameras, the visual sensor at the front end of the daylighting is generally controlled and adjusted with fixed parameters. For advanced surveillance cameras, multiple sets of fixed parameters are used to adapt to various situations. The traditional visual sensor parameter setting adopts the method of combining manual setting and system automatic setting. There are three types of input sources: 1. Human eye recognition. According to human eye discrimination, manually adjust the parameters of the visual sensor. The advantage of this adjustment method is that the adjusted result is more in line with the feel...

Examples

Embodiment Construction

[0016] Control attached figure 1 , the structure of the fuzzy control system includes a fuzzy controller, an input and output interface, a detection device, an actuator and a control object, wherein the signal output end of the detection device is connected to the signal input end of the input interface, and the signal output end of the input interface is connected to the fuzzy control The signal input end of the controller is connected, the signal output end of the fuzzy controller is connected with the signal input end of the output interface, the signal output end of the output interface is connected with the signal input end of the actuator, and the signal output end of the actuator is connected with the control object The signal input end of the control object is connected with the signal input end of the detection device.

[0017] As for the control object, the control object of this system is a visual sensor. The vision sensor is a multivariable, nonlinear, time-varyin...

technical field

[0001] The invention relates to a fuzzy self-adaptive control system of visual sensor parameters, which is suitable for technical fields such as safety monitoring, intelligent transportation, high-definition video conferencing, high-definition medical video diagnosis, and distance education. Background technique

[0002] At present, in ordinary surveillance cameras, the visual sensor at the front end of the daylighting is generally controlled and adjusted with fixed parameters. For advanced surveillance cameras, multiple sets of fixed parameters are used to adapt to various situations. The traditional visual sensor parameter setting adopts the method of combining manual setting and system automatic setting. There are three types of input sources: 1. Human eye recognition. According to human eye discrimination, manually adjust the parameters of the visual sensor. The advantage of this adjustment method is that the adjusted result is more in line with the feel...

Examples

Embodiment Construction

[0016] Control attached figure 1 , the structure of the fuzzy control system includes a fuzzy controller, an input and output interface, a detection device, an actuator and a control object, wherein the signal output end of the detection device is connected to the signal input end of the input interface, and the signal output end of the input interface is connected to the fuzzy control The signal input end of the controller is connected, the signal output end of the fuzzy controller is connected with the signal input end of the output interface, the signal output end of the output interface is connected with the signal input end of the actuator, and the signal output end of the actuator is connected with the control object The signal input end of the control object is connected with the signal input end of the detection device.

[0017] As for the control object, the control object of this system is a visual sensor. The vision sensor is a multivariable, nonlinear, time-varyin...

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