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Method for image identification based on vocabulary tree retrieval and brute-force matching
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An image recognition and vocabulary tree technology, applied in the field of image recognition, can solve problems such as the speed of uploading images, and achieve the effect of improving retrieval speed, improving accuracy, and reducing the amount of data.
Active Publication Date: 2017-06-13
成都弥知科技有限公司
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[0003] However, the current cloud-based real-time image recognition technology uploads local pictures to the server, and the server compares the pictures with recognition with the stored pictures one by one. It has the following defects: in the case of poor wireless networks, users can upload images in real time. The speed of the
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Embodiment 1
[0036] This embodiment discloses a method for generating a cloud image database based on description sub-samples, including the following steps:
[0037] Descriptor generation step: collect images, extract ORB feature points of each image, and generate corresponding descriptors for each ORB feature point to obtain descriptor samples;
[0038] Step of generating a tree model: generating a tree model of the image database according to the description sub-sample;
[0039] Database generation step: adding images to the tree model to establish a tree structure image database.
[0040] specific:
[0041] In the step of generating descriptors, the number of collected images should be many and come from various scenes, generally tens of thousands of images are required, which are stored in a folder, and commonly used image formats are acceptable, such as JPG, JPEG, JPE, JFIF, BMP ; Perform a certain scaling on each image to establish an image pyramid, use the ORB algorithm to extrac...
Embodiment 2
[0054] An image recognition method based on vocabulary tree retrieval and violent matching, comprising the following steps,
[0055] Image acquisition step: acquire the target image, and use the ORB algorithm to extract all ORB feature points on the target image, and generate a corresponding descriptor for each ORB feature point, and generate an ORB descriptor sequence of the target image;
[0056] Image uploading step: upload the ORB description subsequence to the cloud image database based on the description sub-samples;
[0057] Image recognition step: the cloud image database uses the search algorithm of the search vocabulary tree to match and identify the image and return N candidate images with the highest matching degree, where N is a natural number greater than 1; for example, N is 10;
[0058] Brute force matching step: Find the candidate image in the cloud image database, and use the string matching algorithm to perform one-to-one brute force matching on the candidat...
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Abstract
The invention discloses a method for image identification based on vocabulary tree retrieval and brute-force matching. The method comprises an image obtaining step of obtaining an image, using an ORB algorithm on the image to extract all ORB feature points, and generating a corresponding descriptor for each ORB feature point, and generating an ORB description subsequence of the image; an imaging uploading step of uploading the ORB description subsequence into a cloud image database; an image identification step: in the cloud image database, utilizing a search algorithm of a search vocabulary tree to perform matching identification on the image and returning N candidate images with matching scores among the top few; a brute-force matching step of finding the candidate images in the cloud image database, and performing one-to-one brute-force matching on the candidate images and the ORB description subsequence of the image to determine an optimal matching image. Search matching is implemented through extraction of the image descriptor, the influence on an identification speed caused by a poor network is small, and searching precision is high under the conditions that the size of the vocabulary tree structure is limited.
Description
technical field [0001] The invention relates to the technical field of image recognition, in particular to an image recognition method based on vocabulary tree retrieval and violent matching. Background technique [0002] Real-time image search is a real-time image recognition technology that can support user-defined, ultra-large-scale image databases. It can realize real-time recognition of the image input content of the mobile terminal device. The whole recognition process is carried out in the cloud, so that users do not need to download the huge image database locally, and can also make full use of cloud computing resources for high-speed retrieval of the database. [0003] However, the current cloud-based real-time image recognition technology uploads local pictures to the server, and the server compares the pictures with recognition with the stored pictures one by one, which has the following defects: in the case of poor wireless networks, users upload images in real ...
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