Image test method and image test device

Abstract

The invention discloses an image test method and an image test device. The method comprises the following steps: acquiring a test image and a standard image corresponding to the test image; extracting the feature points of the test image and the feature points of the standard image through a scale-invariant feature transform algorithm, and determining a first number of matching feature points from the feature points of the test image and the feature points of the standard image; removing mismatching points from the first number of matching feature points through a random sampling consensus algorithm to get a second number of matching feature points, judging whether the test image and the standard image match each other according to the first number and the second number, and determining a homographic matrix between the test image and the standard image according to the second number of matching feature points after matching; and determining the tensile state of the test image at the time of display according to the homographic matrix.

Description

Technical field [0001] The invention relates to the technical field of image processing, in particular to an image testing method and device. Background technique [0002] In recent years, smart phones have become more and more powerful, mobile terminal applications have emerged one after another, and the mobile Internet has changed people's lives. At present, the more popular smart phone systems include Android, iOS, Windows Phone, etc., and the increasing number of smart phone brands and frequent model updates make their hardware and the configured software or applications different, resulting in mobile phone application compatibility (SoftwareCompatibility) The problem is becoming more and more prominent. [0003] Compatibility testing for mobile phone applications includes interface display testing, resolution compatibility testing, etc. Software testing is a relatively monotonous and boring job. If manual testing can be replaced by software programming, it can greatly improv...

AI Technical Summary

Problems solved by technology

The comparison between the two cannot match, indicating that the business test does not meet the requirements

[0005] However, the existing automated mobile phone testing technology implemented by image comparison has the following defects: it does not adapt well to the diversity of current mobile phone resolutions, adopts a simple scaling mechanism to adapt to multiple resolutions, and cannot effectively and accurately adapt to complex mobile phone screen resolutions The situation; the test adaptability is relatively single, and it cannot adapt to a variety of test environment conditions, or uniformly adopt the same test strategy for different test objects, resulting in low test reliability

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