Spatial pyramid object identification method based on kernel function matching

A space pyramid, object recognition technology, applied in character and pattern recognition, instruments, computer parts and other directions, can solve problems such as increasing the difficulty of object recognition, and achieve good recognition results, rich information, and more points of interest.

Active Publication Date: 2016-06-08
JIANGNAN UNIV
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Problems solved by technology

In addition, the differences between similar objects further exacerbate the difficulty of object recognition

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  • Spatial pyramid object identification method based on kernel function matching
  • Spatial pyramid object identification method based on kernel function matching
  • Spatial pyramid object identification method based on kernel function matching

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Embodiment Construction

[0026] In order to better illustrate the purpose, concrete steps and characteristics of the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings:

[0027] refer to figure 1 , a kind of space pyramid object recognition method based on kernel function matching that the present invention proposes, mainly comprises the following steps:

[0028] Step 1. Collect sample images of objects to be identified, and divide the collected sample image data into training samples and test samples;

[0029] Step 2: Convert the images of the training samples and test samples into grayscale images, and convert the data type of the grayscale images into double-precision floating point types; then scale the size of the image so that its height and width are in [50,200 ]between;

[0030] Step 3, extracting the ED-SIFT (EfficientDenseScale-invariantFeatureTransform) descriptor of the training sample and the test sample;

[...

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Abstract

The invention discloses a spatial pyramid object identification method based on kernel function matching. The spatial pyramid object identification method comprises the following steps of extracting an efficient dense scale-invariant feature transform (ED-SIFT) descriptor of an object image; clustering the ED-SIFT descriptors of a training sample by means of a k-means++ clustering algorithm, obtaining a visual dictionary; introducing a spatial pyramid, obtaining visual word histograms of the training sample and the testing sample by means of kernel function matching; and finishing training sample training and testing sample identification by means of a SVM classifier. The algorithm represented by the invention has relatively high identification degree on image object identification. Furthermore on condition of relatively small number of training samples, high classification effect can be obtained through utilizing the simple SVM classifier.

Description

Technical field: [0001] The invention relates to the field of machine vision, in particular to a space pyramid object recognition method based on kernel function matching. Background technique: [0002] With the rapid development of computer and multimedia technology, the scale of digital images and videos has expanded rapidly. Although massive image data facilitates people's life, it also brings great troubles to people's life. How to quickly and accurately find images of objects of interest to us from massive image data is becoming more and more difficult. Therefore, how to fully and accurately understand images, how to organize image data in an orderly, efficient and reasonable manner, and retrieve the required images has gradually become one of the hotspots in computer vision research. [0003] In recent years, the object recognition algorithm with Bag of Words (BoW) as the key technology has made the most outstanding progress. In recent decades, experts and scholars ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/52
CPCG06V10/42G06V10/758G06F18/23213
Inventor 孔军张迎午蒋敏高坤柳晨华
Owner JIANGNAN UNIV
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