A method for image target recognition in complex underwater environment

Abstract

The invention discloses an image target recognition method used in complex underwater environments, including: step 1: preprocessing the image by using gamma transformation; step 2: extracting the feature of the gradient histogram of the image direction; step 3: according to the blurred image Step 4: Use the support vector machine for training and testing; Step 5: Use the support vector machine trained in step 4 for image recognition. The present invention can overcome the current difficulties of not many underwater image databases, complicated picture backgrounds, and scarce ideal underwater pictures, and reduces the requirements for images in underwater image target recognition using support vector machines, and can also ensure rapidity and Accuracy, while reducing the target feature dimension, avoiding overfitting caused by the number of samples being much smaller than the feature dimension when using machine learning for target recognition, improving the speed and accuracy of underwater target recognition.

Description

technical field [0001] The invention relates to an image target recognition method used in underwater complex environments, belonging to the field of underwater image target recognition. Background technique [0002] Underwater image target recognition is an important branch in the field of image recognition and has broad application prospects. Using traditional machine learning methods for underwater image target recognition does not require a large amount of learning data, which can well solve the problem of insufficient sample data available for underwater images , but at the same time it also brings new troubles. In order to accurately propose target features from a small amount of learning data, it is required to have as few disturbing features as possible in the picture, such as background and lighting, and to have high quality requirements for the picture, otherwise it will affect The accuracy of image target recognition. In order to enable image target recognition t...

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Problems solved by technology

[0002] Underwater image target recognition is an important branch in the field of image recognition and has broad application prospects. Using traditional machine learning methods for underwater image target recognition does not require a large amount of learning data, which can well solve the problem of insufficient sample data available for underwater images , but at the same time it also brings new troubles. In order to accurately propose target features from a small amount of learning data, it is required to have as few disturbing features as possible in the picture, such as background and lighting, and to have high quality requirements for the picture, otherwise it will affect The accuracy of image target recognition

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