红外相机技术在河北雾灵山国家级自然保护区中的应用

为了充实河北雾灵山自然保护区的野生动物资源本底资料,提高监测能力和监测水平,雾灵山保护区自2015年开始将红外相机技术应用到野生动植物的资源调查和管护中。目前应用红外相机技术发现兽类5目10科14种,鸟类4目6科10种,掌握了区内主要物种猪獾(Arctonyx collaris)、狍(Capreolus)和勺鸡(Pucrasia macrolopha)的日活动节律,补充了保护区的本底调查资料,为保护区进一步开展金钱豹(Panthera pardus)、斑羚(Naemorhedus goral)和鸟类多样性等科学研究奠定了基础,为保护区制定关于野生动物资源的相关管护政策提供了科学依据。     

Comparison of Seven Digital Cameras for Digitizing Radiographs

The purpose of this study was to evaluate seven digital cameras for their ability to adequately capture quality radiographic images and their relative cost effectiveness. Radiographs of line pair (LP) phantoms (ranging from 0.6 to 16.6 LP/mm) and a 20-step contrast phantom were photographed at a near distance of 30.0 cm and a far distance (determined for each camera) at which a full 14 x 17 in film filled the viewfinder. Of the seven cameras tested, the Canon EOS-D30 consistently performed the best in LP/mm resolved (7.7 at close distance, 1.4 at far distance) and in contrast latitude (all 20 steps at both close and far distances). The Canon EOS-D30, determined to be the best camera used in this study for photographing radiographic images, is also the most expensive camera that was used. Two cameras, the Nikon Coolpix 995 and the Sony DSC-F707, were very close to the Canon in performance at considerably less cost. Certain inexpensive cameras may not be acceptable choices for teleradiology.     

Determining spatial feed distribution in sea cage aquaculture using an aerial camera platform

Within this paper we describe an unmanned aerial vehicle (UAV) based method to estimate the spatial feed pellet distribution in salmon fish-cages and exploit it within a case study to determine the radial pellet distribution for different rotor spreaders and blower configurations. Compared to previously used methods, capturing pellets thrown from a rotary feed spreader in rows of Styrofoam boxes, the UAV based method is simpler and faster to setup and allows to cover a larger portion of the sea cage surface area. We compare results obtained with the Styrofoam box method with results we obtained by an automatic analysis of aerial videos taken by the UAV during feeding experiments. The employed method helps to gain insight into the spatial feed pellet distribution in full-scale salmon fish-cages where the feeding pipe and actual fixation of the spreader may influence the dynamic behaviour of the feeding system. This can also be seen as a step towards a continuous measuring of the feed pellet distribution, particularly in view of possible future feeding systems that may allow to adapt the feed pellet distribution to the actual fish distribution.     

Remote sensing of biotic and abiotic stress for irrigation management of cotton

The applicability of commercially available remote sensing instrumentation was evaluated for site-specific management of abiotic and biotic stress on cotton (Gossypium hirsutum L.) grown under a center pivot low energy precision application (LEPA) irrigation system. This study was conducted in a field where three irrigation regimes (100%, 75%, and 50% ET_c) were imposed on areas of Phymatotrichum (root rot) with the specific objectives to (1) examine commercial remote sensing instrumentation for locating areas showing biotic and abiotic stress symptomology in a cotton field, (2) compare data obtained from commercial aerial infrared photography to that collected by infrared transducers (IRTs) mounted on a center pivot, (3) evaluate canopy temperature changes between irrigation regimes and their relationship to lint yield with IRTs and/or IR photography, and (4) explore the use of deficit irrigation and the use of crop coefficients for irrigation scheduling. Pivot-mounted IRTs and an IR camera were able to differentiate water stress among irrigation regimes. The IR camera distinguished between biotic (root rot) and abiotic (drought) stress with the assistance of groundtruthing. The 50% ET_c regime had significantly higher canopy temperatures than the other two regimes, which was reflected in significantly lower lint yields when compared to the 75% and 100% ET_c regimes. Deficit irrigation down to 75% ET_c had no impact on lint yield, indicating that water savings were possible without reducing yield.     

基于Arduino的智能送药小车

智能单片机小车由于其智能、方便、快捷,被广泛应用于各行业.本研究的智能送药小车包括了Ardunio mega2560单片机、OpenMv4智能识别装置、寻迹装置、L298N模块、433M无线模块等装置.研究结果表明:智能送药小车通过识别地面安置路线以及相应的病房号,可以自动躲避障碍,自动沿设定的路线行驶,既可以实现单车...     

基于双目立体视觉的重叠柑橘空间定位

果实的精准识别和定位是智能采摘面临的难题之一。基于双目立体视觉,提出了一种针对户外重叠柑橘的三维空间定位方法。首先,从双目左右图像中提取重叠柑橘果实轮廓并进行高斯平滑,通过曲率分析,找出异常的轮廓像素点;其次,依次连接相邻两个异常像素点,分析该线段上的像素点到柑橘轮廓的距离,在相邻两正常线段的交点处完成重叠柑橘轮廓分割,并通过寻找异常线段剔除对应的非柑橘轮廓像素点;再者,采用最小二乘椭圆拟合方法重建柑橘目标轮廓,并获取柑橘的中心;最后,根据双目极线约束和图像相似度,对重叠柑橘中心点进行匹配,并基于视差原理计算柑橘中心的深度值及三维空间坐标,确定重叠柑橘的遮挡关系。户外实验结果表明,所提出的方法定位误差为6.38 mm,满足柑橘采摘机器人户外采摘作业的定位精度要求。     

All-around 3D plant modeling system using multiple images and its composition

In this study, we developed an all-around 3D plant modeling system that operates using images and is capable of measuring plants non-destructively without any contact. During the fabrication of this device, we selected a method capable of performing 3D model reconstruction from multiple images. We then developed an improved SfM-MVS (Structure from Motion / Multi-View-Stereo) method that enables 3D reconstruction by simply capturing images with a camera. The resulting image-based method offers a high degree of freedom because the hardware and software can comprise commercially available products, and it permits the use of one or more cameras according to the shape and size of the plant. The advantages of the image-based method are that 3D reconstruction can be conducted at any time as long as the images are already taken, and that the desired locations can be observed, measured, and analyzed from 2D images and a 3D point cloud. The device we developed is capable of 3D measurements and modeling of plants from a few millimeters to 2.4 m of height using this method. This article explains this device, the principles of its composition, and the accuracy of the models obtained from it.     

基于机器视觉的智能种子分选机设计

针对目前市场上种子分选装置多以传统机械式、半自动式为主,智能化程度不高、分拣准确率较低的问题,基于机器视觉技术设计一种智能种子分选机,主要由传输系统、供料系统、图像采集系统、种子筛选系统和控制系统五大部分构成。以‘郑丹958’玉米种子为研究对象,以种子气流下斜抛的水平距离和传送带传输速度为寻优条件进行试验,确定最优气泵压力值和控制器脉冲频率。对960个种子样本（优质、劣质种子分别为824和136 个）通过目标检测模型进行质量识别,判别种子质量,对种子状态进行标注框选和坐标记录。使用PLC（SIMATIC S7-200 CN,CPU224XP）分选模块控制直动式电磁阀组,对种子进行分选试验。结果表明：1）最优组合气泵压力值为0.3 MPa,控制器脉冲频率为3 175 Hz。2）优质、劣质种子识别率分别为93.69%和91.91%,种子分选率为89.6%。该分选机能够有效满足种子分选要求。     

双目立体视觉在果树采摘机器人中的应用

果树采摘机器人是未来智能农业机械化的发展方向,具有广阔的应用前景。为此,针对果树采摘机器人作业环境的复杂性与定位目标的特殊性,从双目定位的几何模型出发,归纳了双目定位的基本过程,总结了立体视觉的摄像机标定问题,提出变焦距双目视觉定位果实的研究方向,并对双目图像的匹配问题进行了分析。