LAM-D photographic leaf area meter Introduction: LAM-D photographic leaf area meter (computer version) is composed of image acquisition equipment and image processing software. It adopts the newly developed image recognition software of our company, and can image and integrate according to the technology of leaf contour feature extraction, graphic object conversion, edge detection and so on. Quickly obtain parameters such as the measured leaf area, perimeter, and number of wormholes. Compared with the traditional leaf area, the measurement is quicker and easier, the result is more vivid and objective, the data is diverse, and the error caused by human operation is greatly reduced. Technical parameter: Measurement parameters: leaf area, perimeter, large leaf length, large leaf width, rectangularity, concave-convex ratio, sphericity, shape coefficient, number of wormholes, area of wormholes, etc. Scope of application: all kinds of common leaves that are complete or contain wormholes Measuring range: 1-600 square centimeters Blade length: 0-290mm Large leaf width: 0-210mm Measurable wormhole range: not less than 0.1 square centimeters Measurement accuracy: 1% (greater than 30cm2), 2% (less than 30cm2) Host storage: Depends on the hard disk space of the host device, with an average of 1~3MB per group. Stability: Change <±2% within one year Average response time: 100ms Application temperature: -30℃-80℃; relative humidity 0-100% Host parameters: Software system: WINDOWS 7 and above Memory at least: 2GB, 4GB recommended Hard disk: 50GB, 100GB or more recommended Interface: USB-A Image collector parameters: Camera resolution: 2592*1944 pixels Auto/Manual Focus: Manual Fill light: bright LED Stepless dimming: not supported Lens support rod retractable: yes
Introduction: LAM-D photographic leaf area meter (computer version) is composed of image acquisition equipment and image processing software. It adopts the newly developed image recognition software of our company, and can image and integrate according to the technology of leaf contour feature extraction, graphic object conversion, edge detection and so on. Quickly obtain parameters such as the measured leaf area, perimeter, and number of wormholes. Compared with the traditional leaf area, the measurement is quicker and easier, the result is more vivid and objective, the data is diverse, and the error caused by human operation is greatly reduced.
