Method, apparatus and computer readable medium for image processing
An image processing and image expansion technology, applied in the field of computer vision, can solve the problem that the semantic segmentation model cannot produce semantic segmentation results, etc.
Active Publication Date: 2021-08-24
BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD
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However, if the junction of the annotated color blocks is not smooth enough or an object is annotated with the wrong color, it may cause the trained semantic segmentation model to fail to produce desirable semantic segmentation results
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[0023] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the drawings, it should be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein; A more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for exemplary purposes only, and are not intended to limit the protection scope of the present disclosure.
[0024] In the description of the embodiments of the present disclosure, the term "comprising" and its similar expressions should be interpreted as an open inclusion, that is, "including but not limited to". The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be read as "at least one ...
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Embodiments of the present disclosure provide a method, an apparatus, and a computer-readable storage medium for image processing. The method described herein includes determining a first region and a second region in an input image to be processed. The first area is at least partially filled with a first color, the second area is at least partially filled with a second color, and the first area and the second area are adjacent areas having a common border area. The method also includes reducing the first area and the second area such that the reduced first area and the second area no longer include the boundary area. The method also includes expanding the reduced first and second regions such that the border region is filled with at least one of the first and second colors. In this way, the embodiments of the present disclosure can provide accurately labeled training images for a subsequent semantic segmentation model training system, thereby improving the accuracy of subsequent image segmentation.
Description
technical field [0001] Embodiments of the present disclosure relate generally to the field of computer vision, and more particularly, to methods, apparatuses, and computer-readable media for image processing. Background technique [0002] Image semantic segmentation is the basic technology of image understanding, which usually refers to grouping the pixels in the image according to the expressed semantics, so that the content in the image can be identified. Early image semantic segmentation schemes usually perform image segmentation based on the low-level visual information of pixels in the image itself, and their segmentation accuracy is often unsatisfactory. After computer vision entered the era of deep learning, image semantic segmentation technology based on deep learning has been widely used. [0003] Although the image semantic segmentation technology based on deep learning can achieve a rapid segmentation effect compared with the earlier scheme, it has higher require...
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IPC IPC(8): G06K9/00G06K9/32G06K9/46G06V10/56
CPCG06V20/00G06V20/56G06V20/62G06V10/56G06T2207/10024G06T7/12G06T7/149H04N1/3935G06T2207/30252G06V10/267G06T3/40G06T7/11G06T5/30G06T5/50G06T7/90H04N1/393G06V30/274G06T11/001G06T2207/20021G06T2207/20081G06T2207/20192
Inventor 段雄郎咸朋周旺闫淼湛逸飞马常杰金永刚
Owner BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD