Optical fiber image transmission bundle is a passive device that using a certain number of regularly arranged optical fibers to transmit images. In order to ensure its imaging quality

the detection system for the number of optical fibers is optimized based on the machine vision technology. In view of the incomplete image acquisition of the end face of the optical fiber image transmission bundle or the defect of the edge

this paper proposes an edge optimization processing algorithm based on Euler number calculation

which can identify

mark and classify all the edge contours in the image. It not only realizes the accurate detection of the number of optical fibers

but also improves the performance of the algorithm through Graphic Processing Unit (GPU) processing. The algorithms in this paper are debugged and run in the environment of visual studio 2013

Opencv 3.1 and CUDA 10.1. The experimental results show that the detection error rate of the total number of optical fibers in the image is about 0.27%

and the error rate of optimized detection is about 0.03%

which basically meets the design requirements. Moreover

compared with the conventional detection methods

the optimization algorithm proposed in this paper can greatly reduce the selection requirements of threshold and have higher detection efficiency. With the support of Compute Unified Device Architecture (CUDA)

the speed of bilateral filtering is increased by about 20 times

and the optimization algorithm and overall operation time are reduced by nearly 1/2.