Real-time classifying method of plant quarantine larvae

A plant quarantine and classification method technology, which is applied in the field of real-time classification of plant quarantine larvae, can solve the problems that the recognition rate of pests needs to be improved, and achieve the effect of good rotation invariance characteristics, improved recognition rate, and low redundancy

Inactive Publication Date: 2013-09-04
杭州富光科技有限公司
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In the above patent, the compressed sensing algorithm is adopted for the extraction

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  • Real-time classifying method of plant quarantine larvae
  • Real-time classifying method of plant quarantine larvae
  • Real-time classifying method of plant quarantine larvae

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Embodiment Construction

[0034] The present invention will be further explained below in combination with specific embodiments.

[0035] Such as figure 1 As shown, a real-time classification system for phytosanitary larvae, including: image acquisition module, keyboard, FPGA embedded processing and control system, display screen, storage module, wireless communication module and printer. Wherein, the image collection module is responsible for collecting images of larvae. Generally, the image acquisition module includes a micro uniform illumination unit, a zoom micro unit and an image acquisition unit.

[0036] The micro uniform lighting unit is an automatic dimming LED micro lighting system controlled by pulse width modulation (PWM). The reflector of the system adopts a free-form reflector, which can provide uniform lighting conditions for the collection of larval images. The zoom micro unit is used for optical imaging of larvae, and the magnification range is generally 0.7x to 4.5x. The low magnifi...

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Abstract

The invention discloses a real-time classifying method of plant quarantine larvae. The real-time classifying method comprises the following steps: establishing an SVM (Support Vector Machine) classifier; obtaining images of various plant quarantine larvae and respectively extracting characteristics to form a larva characteristic database; utilizing the larva characteristic database to train the SVM classifier; obtaining images of larvae to be detected; after pre-treatment, extracting larva image characteristics and inputting the larva image characteristics into the trained SVM classifier to be subjected to matching and recognition to obtain a classified identification result; after the treatment, adopting a larva bending posture correction method to carry out posture correction on the larvae with bent postures; and utilizing a pseudo-Zernike algorithm to extract pseudo-Zernike invariant moment characteristics of the larva images. The real-time classifying method of the plant quarantine larva disclosed by the invention can rapidly, accurately and timely identify and record larva species, and can find the plant quarantine larvae in real time, so that the real-time classifying method has no pollution to the environment and is high in recognition rate.

Description

technical field [0001] The invention relates to the field of classification and identification of plant quarantine larvae, in particular to a real-time classification method for plant quarantine larvae. Background technique [0002] With the accelerated pace of global economic integration and more and more frequent domestic and foreign trade, alien biological invasion has become a global environmental problem. The vast majority of these harmful alien organisms are insect larvae, which are extremely latent. They are often spread and spread through entry-exit personnel, goods, means of transport, and introduced seeds and fruit trees. Therefore, it is of great practical significance to discover, grasp and identify information of dangerous and quarantine larvae in time. [0003] At present, the taxonomy of exotic larval species mainly relies on morphological characteristics and molecular biology methods. However, these two methods have many disadvantages. For example, the met...

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Application Information

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IPC IPC(8): G06K9/62
Inventor 余桂英高战立徐永明胡兴张钰雰范伟军
Owner 杭州富光科技有限公司
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