Intelligent positioning method for small ceramic tiles based on multi-feature fusion

Abstract

The invention discloses an intelligent positioning method for small ceramic files based on multi-feature fusion. The intelligent positioning method comprises the steps of S1, image acquisition; S2, image preprocessing; S3, feature extraction, S4, image target determination; and S5, ceramic file positioning. In the step of image acquisition, an image is acquired through a high-speed linear array CCD camera. In the step of image preprocessing, gray processing is firstly performed on the image, then filtering and denoising processing is carried out, the filtered image is segmented by adopting an edge detection algorithm, the profile of the small ceramic tile is extracted, and then a profile diagram of the ceramic tile is acquired. In the step of feature extraction, corresponding primitive features are generated based on geometric features of the ceramic tile profile in the profile diagram in the step S2; and a logical AND operation is performed by using a filtered image and the profile mask diagram in the step S2, transferring an operation result diagram into an HSV color space, and color features are generated; and combination features are generated according to the primitive features and the color features. The intelligent positioning method realizes high-precision positioning for the small ceramic tiles at a large FOV (Field of View), thereby providing accurate positioning data for visual inspection and robot grasping. In addition, multiple segmentation units can operate concurrently in a multi-threaded system, and the real-time performance of the system is improved.

Description

technical field [0001] The invention belongs to the technical field of tile positioning and segmentation based on machine vision, and in particular relates to a multi-feature fusion intelligent positioning method for small tiles. Background technique [0002] Ceramic tiles are mass-produced on the production line of the factory, and the fired tiles are uploaded from the conveyor belt to the packaging area. During this process, the position of the tiles is detected and positioned by industrial robots for grabbing, handling and packing, which involves For tiles of different sizes, they need to be analyzed and packaged separately. At present, there are two positioning methods for tile detection: one is to manually locate online with the help of measuring tools and experience, and the other is to install sensors with the help of specially designed mechanical structures (that is, industrial robots). ) to complete the positioning. Manual detection is affected by factors such as o...

AI Technical Summary

Problems solved by technology

Manual detection is affected by factors such as operator experience, measurement tools, and fatigue, which inevitably leads to positioning errors

Mechanical positioning is mainly due to the fact that the mechanical structure cannot adapt to various types of tiles, which requires high positioning costs and poor adaptability, especially for small-sized tiles under a large field of view (Field of View), because the current FOV cannot be estimated The number of small tiles and the uncertainty of the movement position, the above two methods cannot meet the positioning needs of small tiles

At present, there are still relatively few researches on high-precision positioning methods for small tiles by major scientific research institutes and colleges in China. Therefore, in view of the problems of high cost, poor adaptability and low precision of traditional positioning methods, the development of intelligent positioning methods for small tiles has become an inevitable trend of automatic detection.

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