Goods image segmentation method and device
A commodity image and pixel point technology, applied in the field of image processing, can solve the problems of large amount of calculation, time-consuming, low segmentation efficiency and low segmentation accuracy, and achieve the effect of high accuracy and efficient operation speed
Inactive Publication Date: 2018-05-08
广州图普网络科技有限公司
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The segmentation efficiency and segmentation accuracy of the method of artificially setting the foreground on the picture are very low, while the method of superpixel segmentation of the image and the method of mapping the entire image requires a large amount of calculation and is very time-consuming
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[0069] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.
[0070] In one embodiment, such as figure 1 As shown, a method for commodity image segmentation is provided, which specifically includes the following steps:
[0071] Step 102: Obtain the image of the target product.
[0072] The target product image is a product image that needs to be segmented from the foreground and background. The foreground can be the product itself, or the foreground can be a person. For example, when the product is clothes, the product image can be segmented into people and background.
[0073] Step 104: Preprocessing the image of the target product to obtain multi-channel ...
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The invention relates to a goods image segmentation method and device, and the method comprises the steps: obtaining a target goods image; carrying out the preprocessing of the target goods image so as to obtain the multichannel color feature data of all pixels of the target goods image; inputting the multichannel color feature data into a neural network model for processing; obtaining the foreground probability and background probability of all pixels in the target goods image, wherein the neural network model is obtained through the iterative training of a goods image sample seat after preprocessing; obtaining a foreground image and a background image of the target goods image according to the foreground probability and background probability of all pixels in the target goods image, so as to achieve the segmentation of the target goods image. The method and device can achieve the automatic, accurate and efficient segmentation of the goods image.
Description
technical field [0001] The present invention relates to the field of image processing, in particular to a commodity image segmentation method and device. Background technique [0002] With the rapid development of computer vision technology, image segmentation has attracted widespread attention and is a key issue in computer vision. Image segmentation is the technology and process of dividing an image into several specific regions with unique properties and proposing objects of interest. It is a key step from image processing to image analysis. The purpose of image segmentation is to simplify or change the representation of the image, making the image easier to understand and analyze. [0003] In the processing of commodity images, the image segmentation process mainly divides the image into foreground and background parts. For example, the street took an image of a stylishly dressed pedestrian. In this image, the stylishly dressed pedestrian is the foreground of the image...
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Login to View More IPC IPC(8): G06T7/11G06T7/136
CPCG06T2207/10024G06T2207/20016G06T2207/20081G06T2207/20084
Inventor 李明强
Owner 广州图普网络科技有限公司