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Image classification method based on visual attention model

A technology of visual attention model and classification method, applied in the field of image classification based on visual attention model, can solve the problems of large redundancy and interference.

Inactive Publication Date: 2009-03-11
SHANGHAI JIAO TONG UNIV
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  • Description
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Problems solved by technology

This method has an obvious defect, that is, the extracted features of each sub-block of the entire image are not filtered, so the extracted features must contain information about the various components of the image including the target and background, so there is a large redundancy and interference

Method used

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  • Image classification method based on visual attention model
  • Image classification method based on visual attention model

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Embodiment Construction

[0044] The embodiments of the present invention are described in detail below in conjunction with the accompanying drawings: this embodiment is implemented on the premise of the technical solution of the present invention, and detailed implementation methods and specific operating procedures are provided, but the protection scope of the present invention is not limited to the following the described embodiment.

[0045] The image database used in this embodiment is the Caltech image database, which includes 6 categories of faces, airplanes, car tails, car bodies, motorcycles and backgrounds. Each category has relatively large intra-category differences and the background is messy.

[0046] Such as figure 1 As shown, this example includes the following steps:

[0047] Step 1: Randomly select 50% of each of the 6 categories in the Caltech image library as training samples and 50% as testing samples.

[0048] Step 2, extract the feature vector of each training sample based on t...

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Abstract

The invention discloses a method of image classification based on a visual attention model in the technical field of image classification. The method of the invention comprises the following steps: step 1: certain quantity of images are randomly selected from a selected image database to be used as training samples; step 2: a characteristic vector of each image based on the visual attention model and the overall scarcity is captured; step 3: a characteristic vector of each image based on the visual attention model and the overall scarcity is calculated to the image to be classified; and step 4: the characteristic vectors captured in step 2 and step 3 are transmitted to a classifier to be classified; finally, the result of the classification of the image to be classified is obtained. The method can classify the image by capturing visual characteristic characters at a high level from the characters at a bottom level so as to ensure more precise result of the classification.

Description

technical field [0001] The invention relates to a method in the technical field of image classification, in particular to an image classification method based on a visual attention model. Background technique [0002] The visual selective attention mechanism of the human eye is to enable us to quickly locate the target of interest in a complex visual environment. Attention uses an information-processing bottleneck mechanism that allows only a small fraction of information entering sensory organs to reach short-term memory and visual attention areas. If a certain visual stimulus (object) is salient enough, it will stand out from a frame. This saliency has nothing to do with the purpose of observation, and it works in a fast, bottom-up manner. [0003] Image classification, that is, image category recognition is a subject that emerged with the development of computers, and has now penetrated into various fields. Such as research on chromosomal characteristics in biology; tel...

Claims

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Application Information

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IPC IPC(8): G06K9/66G06F17/30
Inventor 张瑞杨小康宋雁斓陈尔康支琤
Owner SHANGHAI JIAO TONG UNIV
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