Abstract:

Objective: In this study, a forest pinecone detection method based on real-time detection transformer (RT-DETR) was proposed to address the challenges of complex forest environments, small pinecones with indistinct texture features, leading to insufficient detection accuracy and poor real-time detection performance. The RT-DETR model has been optimized to enhance detection performance. Method: Firstly, to improve detection accuracy, the original backbone network was replaced with the re-parameterized vision transformer (RepViT) to enhance feature extraction capability. Secondly, the high-low frequency feature interactions (HiLo) mechanism was introduced to improve the capture of fine texture details. Finally, the re-parameterized cross stage partial bottleneck with 3 convolutions (RepC3) module was optimized into the decoupled replicated bottleneck cross stage partial with 3 convolutions (DRBC3). The receptive field was significantly expanded by incorporating large kernel convolutions and dilated convolutions. Meanwhile, both RepViT and DRBC3 adopted structural re-parameterization designs, simplifying the model structure during inference, and thus improving detection efficiency. Result: The optimized RT-DETR model was tested on the pinecone image dataset collected from Dalai forest station in Jiamusi, Heilongjiang Province, China, and the result showed that all metrics of the model achieved optimal balance, with AP50 of 93.37%, a precision of 93.30%, and a recall of 92.65%. While AP50 improved by 5%, GFLOPs were reduced by 51%, the number of parameters decreased by 41%, and the real-time frame rate FPS significantly increased from 74.3 to 95.5, representing a 28% improvement. Conclusion: This optimization method significantly improves the accuracy, real-time performance, and efficiency of pinecone detection in forest environments, providing an effective solution for automated pinecone harvesting tasks in practical applications.

Key words: RT-DETR, pinecone detection, RepViT, HiLo high-low frequency separation mechanism, DRBC3