Method for shooting and taking evidence through handheld camera

Abstract

The invention relates to an image evidence-taking technology. The invention aims at adopting the bevel angle of a blanking line, which is obtained by computing, to perform the certification of camera shooting modes, and adopts the technical scheme that the method for shooting and taking evidence through a handheld camera comprises the following steps of: firstly, extracting linear information of an original image, secondly, positioning a corresponding blanking point according to the extracted linear information, thirdly, computing the rotation angle of a camera, and fourthly, performing the certification of shooting modes according to the rotation angle. The method is mainly applied to image forensics.

Description

technical field [0001] The invention relates to image forensics technology, belongs to the field of computer image content security, and relates to a method for calculating the rotation angle of a camera. Specifically, it relates to a method for taking evidence with a hand-held camera. Background technique [0002] With the rapid development of mobile handheld devices and the Internet, data acquisition, especially image data, has become easier and easier, but the requirements for image information processing are also getting higher and higher. Pictures are the most intuitive expression of recording culture. In addition to the intuitive information contained in the pictures, other hidden clues should also be given equal attention, such as the authentication of the way the pictures were taken. Aiming at the above problems, a general calculation method of camera rotation angle proposed by the present invention provides a feasible solution. [0003] For the detection of the pi...

AI Technical Summary

Problems solved by technology

[0006] For digital images, the currently commonly used detection algorithms for blanking points are: the first type uses statistical methods to estimate line parameters according to image edge features, and then uses the obtained parameters to calculate blanking points [1]. Although it has an advantage in theory, the time complexity of the algorithm is high, and the efficiency cannot meet the needs of practical applications.

The second type mainly transforms some information of the image into a limited space, and uses space transformation to transform the hidden points at infinity and finite distances into equivalent ones, but after this processing, the lost Information such as the length of the line segment and the distance of the blanking point

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