Circular loop statistic characteristic-based anti-rotation image Hash method

Abstract

The invention relates to a circular loop statistic characteristic-based anti-rotation image Hash method, which comprises the following steps of: normalizing the size of an image size by using a bilinear interpolation method; processing the image by using a Gaussian low-pass filter; if the image is a color image, converting the image into a YCbCr color space, and representing the color image by using a brightness component; dividing the image into a plurality of circular loops, and extracting statistical data such as an average value, variance, skewness degree and kurtosis of each circular ring as characteristics; normalizing the statistical characteristics; calculating an average value of the statistical data, taking the average value as a reference, calculating Euclidean distances between the statistical characteristics of the circular loops and reference characteristics, and connecting all distance values in series to obtain an image Hah; and when similarity is judged, calculating L2 norms of two Hashes, determining that corresponding images are the same if the similarity is less than a set threshold value, otherwise determining that the corresponding images are different. The method is robust for common digital processing such as image rotation, joint photographic experts group (JPEG) compression, noise jamming, brightness regulation and contrast enhancement, and is high in uniqueness.

Description

technical field [0001] The invention relates to the field of signal processing and computer technology, in particular to an anti-rotation image Hash method based on circular statistical features. Background technique [0002] The emergence of various powerful and easy-to-operate image processing software, such as Photoshop and ACDSee, has made digital image editing operations easier and easier, leading to increasingly serious image infringement problems such as tampering and forgery, and image content copyright protection and integrity Certification becomes an urgent matter. At the same time, the large-scale growth of digital images urgently requires more effective technologies to achieve efficient retrieval and management of massive image data. In recent years, a new technology called image Hash has emerged in the field of digital media content processing, which can be widely used in image retrieval, copy detection, content authentication, tamper detection, digital waterma...

AI Technical Summary

Problems solved by technology

[0005] Most of the above-mentioned existing technologies are robust to certain digital processing, such as JPEG compression, digital filtering, image scaling, and brightness adjustment, but they are generally fragile to rotation operations and have the disadvantage of poor uniqueness

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