Abstract

In order to detect small cracks on the surface of casting workpieces in real time, this paper proposes a feature fusion target detection algorithm based on SSD network. First, the image is reshaped and fed into the network to generate multiple feature maps of different scales. First, the image is resized and fed into the network to generate multiple feature maps of different scales. Feature fusion is performed between feature maps to generate new feature maps. Finally, multiple new feature maps are used to predict crack coordinates and probability. After experimental testing, the detection speed of the algorithm in this paper reaches 87fps, while the accuracy rate reaches 92.3%, indicating that the algorithm has high detection accuracy and speed.

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