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Received Jan 2, 2018; Accepted Mar 25, 2018
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1. Introduction
Image similarity detection is a hot issue in the field of multimedia information processing. Similar image is a set of images obtained from an image of the same scene or the same object taken from different environmental conditions such as different angles or different lighting conditions and edited transformations of the same original image through different ways. Examples of some similar images are shown in Figure 1.
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Image similarity detection is to judge the similarity of visual content by matching the image. According to the adopted feature, image similarity detection methods can be divided into two categories, namely, global-feature-based detection methods and local-feature-based detection methods. The global feature of the image refers to the use of one or a few feature vectors to represent whole image content. Common global features include color histograms, texture features, and block features. Because the number of feature points is small, the calculation speed of image content similarity detection based on global feature is usually very fast. However, due to the singularity of its feature selection and the roughness of the description image, the global feature is very susceptible to edits and local transformations. For example, image similarity detection with color histogram as global feature is very sensitive to the illumination of the image. Usually, similar images are created by editing transformation; similarity detection accuracy is generally relatively low based on the global features of the image content.
In recent years, some scholars have proposed local features for image similarity detection. Compared with global features, local features of the image usually have some local invariance for the illumination, rotation and scaling of the image and have been widely applied in the field of content-based image and video retrieval. Local feature points are usually local extreme points in an area of the image, and have more obvious features than the rest of the pixels in the region. Description of the local feature points is generally the combination of the characteristics of the key points and the...