Firework identification method and firework identification system based on deep learning of image

Abstract

The invention discloses a firework identification method and a firework identification system based on deep learning of an image. The firework identification method comprises the following steps of step 1, acquiring a label-free sample image set and a label sample image set; step 2, obtaining a label-free training data set and a label training data set; step 3, performing whitening preliminary processing on training data; step 4, based on the label-free training data subjected to the whitening preliminary processing, constructing a deep neutral network based on sparse self coding by adopting unsupervised learning, and extracting a basic image feature set of the label-free training data; step 5, convolving basic image features and pooling image data; step 6, training a Softmax classifier based on the convolved and pooled label training data set; step 7, inputting the convolved and pooled images to be identified into the trained Softmax classifier to obtain the identification result. According to the firework identification method and the firework identification system disclosed by the invention, the visual identification rate of fireworks and a similar object can be effectively improved, and automatic identification with higher precision for the fireworks can be realized.

Description

technical field [0001] The invention belongs to the technical field of fire intelligent monitoring and pyrotechnic target automatic recognition based on digital images, and in particular relates to a pyrotechnic recognition method and system based on image deep learning. Background technique [0002] The intelligent monitoring of pyrotechnics based on digital images is a classic problem related to image processing, computer vision, artificial intelligence, machine learning and many other fields. At present, there are some literatures on automatic recognition of pyrotechnic objects. The recognition process can generally be divided into target segmentation, feature Extraction, comprehensive judgment and other stages. [0003] Phase 1, target segmentation. [0004] Pyrotechnic automatic target segmentation can be roughly divided into threshold segmentation, edge detection segmentation, region characteristic segmentation, feature space clustering segmentation and other methods....

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Problems solved by technology

So far, no research has combined deep learning with pyrotechnic recognition

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