Color image search method based on scale invariant feature transform (sift) seed region growing

A technology of region growth and color images, applied in the computer field, to achieve good robustness, strong robustness, and improved accuracy

Active Publication Date: 2013-05-22
SUZHOU VOCATIONAL UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] The technical problem mainly solved by the present invention is to provide a color image retrieval method based on sift seed region growth, w

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  • Color image search method based on scale invariant feature transform (sift) seed region growing
  • Color image search method based on scale invariant feature transform (sift) seed region growing
  • Color image search method based on scale invariant feature transform (sift) seed region growing

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Embodiment 1

[0044] Embodiment one: figure 1 It is a flow chart of a color image retrieval method based on SIFT seed region growth implemented by the present invention, and the image files are all color images.

[0045] 1. Select the sift seed point in the image to generate a sift seed point set E . Specific steps are as follows:

[0046] 1. Use the sift algorithm to detect local extremum points in the Gaussian scale space, then use the principal curvature of the Gaussian difference operator to delete edge response points in the local extremum points, and use the retained local extremum points as candidate feature points. Finally, the position of each candidate feature point in the original image is calculated.

[0047] 2. Use the Canny edge detection algorithm to detect the edge feature points of the image. Calculate the position of the pixel points within the 3×3 field of each edge feature point.

[0048] 3. If the position of the candidate feature point is not within the 3×3 area ...

Embodiment 2

[0080] Embodiment two: In order to illustrate the preference of using the region growing method based on the sift seed point to segment images in embodiment one, Figure 4 The method of the present invention is given. In the second step of the method of the present invention, the method of manually segmenting the image while other steps remain unchanged, and directly extracting the color sift feature and Hu invariant moment feature of the image without segmenting the image are used for image retrieval. The precision-recall trend chart of the method. The recall rate refers to the ratio of the number of correct images retrieved from the image library to the number of images in the image library that are consistent with the category of the image to be queried.

[0081] according to Figure 4 As a result, the method of the present invention uses the region growing method based on the sift seed point to segment the image, and then uses the KM algorithm to solve the optimal matchin...

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Abstract

The invention discloses a color image search method based on scale invariant feature transform (sift) seed region growing. The color image search method based on the sift seed region growing comprises the following steps: (1) choosing a sift seed point for an image to be detected; (2) dividing the image in to a plurality of regions by the adoption of a region growing method; (3) combining the regions according to the rule; (4) aiming at each region to extract a region characters; (5) calculating the similarity between regions of images in an image library and the region of the image to be detected; (6) structuring a weight bipartite graph; calculating the similarity between the image to be detected and the images in the image library; (7) arranging the images in the image library in descending order according to the similarity of the image to be detected. By the adoption of the mode, the color image search method based on the sift seed region growing can reduce the error problem due to inaccuracy of the images division and make up the defect that a single character search image is used.

Description

technical field [0001] The invention relates to the computer field, in particular to a color image retrieval method based on SIFT seed region growth. Background technique [0002] As a kind of multimedia information with rich connotation and intuitive expression, image is favored by people. More and more business activities, business transactions and information representations contain image data. Especially in the popular electronic shopping on the Internet, the information of products is basically shown to users in the form of images. [0003] Traditional image retrieval methods use the underlying features of images, such as color, texture, shape, and spatial relationship, and these features have their own shortcomings. The color feature is not sensitive to changes in the direction and size of the image or image area, and cannot capture the local features of the object in the image well, nor can it express the information of the color space distribution; The texture ref...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06T7/00
Inventor 杨元峰李金祥鲜学丰廖黎莉李亚琴
Owner SUZHOU VOCATIONAL UNIV
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