Image characteristic extraction method

An image feature extraction and image technology, which is applied in the field of image processing, can solve the problems of ignoring pixel position information, misjudgment, and large amount of calculation, and achieves the effect of reducing the amount of calculation, improving performance, and improving accuracy.

Active Publication Date: 2010-07-07
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

However, when this technology calculates, every pixel in the image is treated equally, and the position information of the pixel is ignored, which leads to a considerable amount of calculation.
[0005] After retrieval, it is found that the article "Image retrieval based on shape similarity by edge orientation autocorrelogram (based on Image retrieval

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Embodiment

[0030] The image database used in this embodiment is all video key frames of TRECVID2005. TRECVID is an authoritative competition in the field of video retrieval held by the National Institute of Standards (NIST), and 16 semantic concepts were selected for detection. The entire image database has a total of 60,422 images, which are divided into two parts: the training image library and the image set to be detected. Among them, there are 42,226 images in the training image library, including 5,039 positive samples and 37,187 negative samples. The image set to be tested has a total of 18196 images, including 2055 positive samples and 16141 negative samples.

[0031] This embodiment includes the following steps:

[0032] The first step is to extract the position information and RGB color components of all pixels in the image I.

[0033] In the second step, the RGB color components of each pixel are transformed into HSV color components, and the three components of HSV are non-u...

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Abstract

The invention discloses an image characteristic extraction method in the technical field of image processing, which comprises the following steps: extracting position information and color information of all pixel points in an image; performing edge area processing on the image, and acquiring position information and color information of each pixel point in the edge area; extracting color self-correlation characteristics from the edge area of the image I, and acquiring a color self-correlation diagram of the edge area; extracting edge direction self-correlation characteristics from all the areas of the image, and acquiring a global edge direction self-correlation diagram; extracting color self-correlation characteristics from all the areas of the image, and acquiring a global color self-correlation diagram; and performing characteristic pre-fusion on the three self-correlation diagrams, and acquiring image characteristics. The image characteristic extraction method realizes more comprehensive image structure-based content description through the characteristic fusion, reduces the computed amount, improves the performance, and has higher accuracy during image retrieval.

Description

technical field [0001] The present invention relates to a method in the technical field of image processing, in particular to an image feature extraction method. Background technique [0002] With the rapid development of multimedia technology and computer networks, the scale of multimedia databases such as digital images has expanded rapidly. In the face of a large number of images distributed in disorder, the traditional retrieval method based on text keywords can no longer meet the needs of users. In order to find images quickly and accurately, in the early 1990s, content-based image retrieval technology (CBIR: content-based image retrieval) came into being. Different from the search method of querying and matching manually marked keywords in the original system, the content-based retrieval technology automatically extracts the visual content features of each image as its index, such as color, texture, shape, etc. Images are sorted by similarity of visual features and r...

Claims

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Application Information

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IPC IPC(8): G06K9/46G06F17/30
Inventor 杨小康张瑞陈晓琳
Owner SHANGHAI JIAO TONG UNIV
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