基于苗床平面对准和高效点线匹配的温室草莓苗床图像拼接方法

IF 7.7 1区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY
Jiong Lin , Xue Bai , Mengen Yuan , Dong Wang , Shuqin Yang , Jifeng Ning
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引用次数: 0

摘要

在温室草莓苗木工厂化栽培的背景下,获取苗床的全景图像对于监测草莓苗木的整体生长至关重要,包括评估生长均匀性和检测病虫害的存在。提出了一种基于苗床平面对准和高效点线匹配的温室苗床图像拼接新方法,利用安装在苗床上方的轨道检测装置对覆盖苗床区域的序列图像进行采集,从而获得高质量的草莓苗床全景图像。首先,由于草莓幼苗位于苗床区域内,因此利用Depth-Anything模型提取苗床平面,使配准算法专注于苗床区域的精确对准。其次,为了充分利用草莓苗床图像的几何结构,采用基于点线匹配的局部配准方法GlueStick对重叠苗床图像之间的特征点进行匹配,在显著减少特征点数量的同时有效提高了匹配精度。最后,利用轨道成像装置的等距成像特性,提出了一种单应性矩阵优化方法,有效缓解了局部匹配少量不准确对全局拼接性能的影响。在构建的草莓苗床图像数据集上进行了主观(定性评分)和客观(RMSE,图像失真度)评价的综合实验,结果表明,该方法实现了苗床的精确对齐,并有效地保持了整体的自然度,优于代表性的图像拼接方法。该方法为苗床监测提供了高质量的全景图像,为温室作物的精确监测提供了有力支持,并为其他温室作物的全景拼接方法提供了有价值的参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A greenhouse strawberry seedbed image stitching method based on seedbed plane alignment and efficient point-line matching
In the context of factory-based cultivation of strawberry seedlings in greenhouses, acquiring panoramic images of the seedbed is essential for monitoring the overall growth of the strawberry seedlings, including assessing the uniformity of growth and detecting the presence of pests and diseases. This paper presents a novel greenhouse seedbed image stitching method based on seedbed plane alignment and efficient point-line matching, using a rail-based inspection device mounted above the seedbed to capture sequential images covering the seedbed area, in order to obtain high-quality panoramic images of the strawberry seedlings. First, since the strawberry seedlings are located within the seedbed area, the Depth-Anything model is utilized to extract the seedbed plane, allowing the registration algorithm to focus on the precise alignment of the seedbed region. Secondly, to fully leverage the geometric structure in the strawberry seedbed images, a local registration method GlueStick based on point-line matching is applied to match feature points between overlapping seedbed images, significantly reducing the number of feature points while effectively enhancing matching accuracy. Finally, exploiting the equidistant imaging characteristics of the rail-based imaging device, a homography matrix optimization method is proposed, effectively mitigating the impact of a small number of inaccurate local matches on the global stitching performance. Comprehensive experiments, encompassing both subjective (qualitative scoring) and objective (RMSE, Image Distortion Degree) evaluations, conducted on the constructed strawberry seedbed image dataset, demonstrate that the proposed method achieves precise alignment of the seedbed and effectively preserves the overall naturalness, outperforming representative image stitching methods. The proposed method delivers high-quality panoramic images for seedbed monitoring, offering substantial support for precise monitoring of greenhouse crops, and provides valuable references for panoramic stitching methods of other greenhouse crops.
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来源期刊
Computers and Electronics in Agriculture
Computers and Electronics in Agriculture 工程技术-计算机:跨学科应用
CiteScore
15.30
自引率
14.50%
发文量
800
审稿时长
62 days
期刊介绍: Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.
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