Method and system for automatically detecting and repelling targets

Abstract

The invention provides an automatic target detecting and expulsing method. The method includes the following steps: a step of target detecting, namely the step of obtaining a target detecting image, and performing image processing on the target detecting image according to data of a database and / or modeling parameters; a step of target capturing, namely the step of obtaining a target capturing image, capturing a target geographic coordinate according to the target capturing image, and performing expulsion on a target according to the target geographic coordinate; and a step of information fusion, namely the step of fusing the target detecting image and the target capturing image to determine a target position. Through the design of a system which combines radar, a panoramic photoelectric camera and a variable focus photoelectric camera, bird expulsing equipment can be automatically started to drive birds away on the premise of detecting the location and quantity of the birds, and therefore, the purpose of automatic bird expulsing can be achieved.

Description

technical field [0001] The present invention relates to a method, in particular to a method and system for automatically detecting an expulsion target. Background technique [0002] Bird strikes are an international problem that has plagued human beings and threatened flight safety for a long time. With the development of aviation, the number of aircraft and flight routes have increased. At the same time, with the expansion of the scope of human activities, the natural environment suitable for birds to live, inhabit and reproduce has been greatly reduced, and the airport has become an ideal place for birds to live, inhabit and reproduce. A certain amount of economic loss, the most serious is the destruction of the aircraft. Birds are friends of human beings and play an important role in the ecological balance. Humans should solve airport bird damage on the premise of not harming birds or harming birds as little as possible. This has virtually increased the difficulty of im...

AI Technical Summary

Problems solved by technology

[0006] This program proposes a vector machine-based airport intelligent bird-repelling decision-making algorithm, support vector machine (SupportVector Machine, SVM), which has many advantages in solving small sample, nonlinear and high-dimensional pattern recognition, but it has two A disadvantage: (1) The SVM algorithm is difficult to implement for large-scale training samples, because SVM uses quadratic programming to solve support vectors, and solving quadratic programming requires the calculation of m-order matrices (m is the number of samples), When the number of m is large, the storage and calculation of the matrix will consume a lot of memory and time

(2) It is difficult to use SVM to solve multi-classification problems. The classic support vector machine algorithm only gives a two-class classification algorithm, but in the practical application of data mining, it is generally necessary to solve multi-class classification problems

[0008] The method used in this program is a fixed passive bird repelling method, which does not have the ability to carry out purposeful driving of birds based on the activities of birds at the airport. Classes are prone to habitual reflexes, which make bird repellent equipment ineffective

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