Automatic clustering, visual and retrieval system for tongue picture based on self-organizing map neural network

Abstract

The present invention discloses an automatic clustering, visual and retrieval method for a tongue picture based on a self-organizing map neural network, which comprises the steps of: (1) obtaining a sample image of the tongue picture by acquisition equipment, conducting tongue segmentation to the sample image and then obtaining a complete tongue picture; (2) extracting the histogram of each component of the tongue picture in an HSV color space, obtaining the feature vector describing the tongue picture sample and then simplifying the dimension of the feature vector; (3) using the feature vector of a typical tongue picture sample to train the self-organizing map neural network for obtaining self-organizing map grids corresponding to the typical tongue picture sample set; (4) retrieving a clustering center which is the most similar to the sample image of the input tongue picture according to the minimum distance criteria, and then retrieving and displaying a sample which is the most similar to the sample image from all the tongue picture samples belonging to the clustering; and (5) highlighting a neuron node corresponding to the matched clustering on the two-dimensional output grids of the self-organizing map neural network and displaying all the samples of the clustering. The system can achieve a clustering, visual and rapid retrieval method for the tongue picture of a large-scale tongue picture sample set.

Description

technical field [0001] The invention relates to a method for automatic clustering, visualization and retrieval of tongue images, in particular to a fast retrieval method based on self-organizing mapping neural network for clustering, visualization and image content of tongue images. Background technique [0002] In TCM diagnostics, tongue diagnosis is one of the important ways to obtain information about the patient's physical status. Tongue diagnosis in traditional Chinese medicine relies heavily on the subjective judgment and personal experience of doctors, which is relatively random and uncertain. By clustering the tongue image data and realizing the visualization of the clustering results, it can help Chinese medicine experts understand the internal structure of the tongue image data, and eliminate randomness and uncertainty to the greatest extent. Using content-based image retrieval technology, according to the current patient's tongue image, retrieve typical sample to...

AI Technical Summary

Problems solved by technology

However, these methods prepare categories and classifiers in advance, and introduce factors of subjective observation of the human eye, such as artificially dividing the tongue color into red, light red, light white and other categories. These artificial factors affect the objectivity of the classification results; At the same time, simple classification results are not enough to fully display the differences and connections between tongue image samples

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