Loral Corporation

Firooz A Sadjadi

Stephen M Sohn

Michael E Farmer

A smart weed recognition and identification system comprises a chlorophyll sensor for detecting green vegetation and memory map means for storing images which contain different forms of green vegetation. The memory maps stored in memory are processed to eliminate the background information and leave a memory map containing only green vegetation. The enhanced memory map is further processed by an operation of segmentation into identifiable regions and the identifiable green vegetation regions are processed to identify unique attributes for each of the regions. The unique attributes for each of the regions is stored in a reference data base library and are used as reference data for comparing other green vegetation with the data stored in the base model by a processor which matches green vegetation in other regions with the green vegetation stored in said reference data base model and further produces decision data signals which are used by a controller to control a plurality of spray nozzles covering the area sensed and for dispensing a plurality of selectable controlled chemicals.

Smart weed recognition/classification system

A polarization diverse image sensor identifies different objects of green vegetation and produces a vegetation index of such vegetation. The sensor defines the degree, angle and intensity of polarization. This information is stored in a memory for producing an image memory map of the polarized pixel data. Differential pixel data is computed and then employed to generate a new polarization difference image which is further processed by histogramming slices of the new image to obtain a segmented image of the green vegetation. The attributes of the segmented image are then compared with segmented data which was previously stored in a model base library to obtain a match or no match of the identification of the green vegetation. If match is obtained, a controller issues control signals which controls the spray heads and chemicals carried on a moving spray platform. However, if no match is obtained, the original raw data is labeled, formatted and stored in the model base library as reference data. The generated data is stored in the memory base library for further analysis or for use in real time control of a utilization device that treats the green vegetation previously that was recognized and identified.

Polarization diverse infrared object recognition system and method

An apparatus and method for on-the-go measuring of the amount and quality of grain being harvested including a first light source for projecting a first light image onto a pile of grain on a conveyor in a harvesting machine to cream a three-dimensional light image on the pile of grain on the conveyor and then converting the light image into coordinates for comparison to reference coordinates to determine the volume of the pile of grain on the conveyor belt; and an apparatus for determination of the amount of moisture in the pile of grain by projecting a second light image of a first wavelength onto the pile of grain, with the wavelength of the light of a frequency responsive to the amount of moisture in the pile of grain, and measuring the amount of reflectance of the light image of the first wavelength; and projecting a third light image of a second wavelength on the pile of grain, with the second wavelength of light in a region where reflectance is not responsive to the amount of moisture in the pile of grain, measuring the amount of reflectance of the light image of the second wavelength comparing the ratio of reflectance of the light image of the first wavelength to the reflectance of the light image of the second wavelength to determine the amount of moisture in the pile of grain and location-measuring equipment for determining an area of standing crop harvested.

Growing community of inventors

Minneapolis, MN, United States of America

Firooz A Sadjadi