Target detection method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a target detection method and device, electronic equipment and a storage medium, relates to the technical field of image processing, can reduce an image without coding and decoding, and does not affect the detection performance of a target object in the reduced image. The target detection method comprises the following steps: carrying out color coding on an input original color image to obtain a plurality of images of a YUV color space; performing pixel region division on a target image in the plurality of images to obtain a plurality of pixel regions corresponding to the target image; carrying out discrete cosine transform on each pixel region to obtain transformation features of the target image; selecting a target channel of a low-frequency region from the transformation features; and performing object detection according to frequency domain feature information of the target channel in the target image.

Description

technical field [0001] The present application relates to the technical field of image processing, and in particular to a target detection method, device, electronic equipment and storage medium. Background technique [0002] The target detection task is an important task in the field of computer vision, and its working purpose is to accurately locate a specific target object from the image through computer image processing. To achieve this purpose by computer, on the one hand, it is necessary to be able to determine the target, for example, to obtain the contour curve of the target, or to obtain parameters such as the shape and size of the target; on the other hand, it is also necessary to locate the target in the image specific location in . As the basic tasks of subsequent segmentation, tracking, and recognition tasks, the target detection task is also an important part of image processing in the field of computer vision. and other links to provide a better data basis. ...

AI Technical Summary

Problems solved by technology

[0003] In practical applications, the video stream is usually input through the camera, because the picture changes presented by the video stream are realized by the sequential transformation of multiple frames of digital images, and for each frame of digital images, it contains Multiple pixels, the resolution of the image is reflected by the number of pixels set in two directions perpendicular to each other. The higher the resolution of the image, the larger the information data carried by the image. Usually the data volume of the original video stream is It is large, which is not conducive to processing, transmission and storage. The encoding and decoding of video streams greatly limits the performance of the algorithm. In order to balance the problem of limited computing power, it is generally necessary to reduce the large-resolution image, but directly reduce the resolution of the image. On the one hand, it will consume the time of data calculation and processing. On the other hand, if the image is directly reduced, it is easy to lose the information of small objects in the image. detection performance is poor

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