IP Library Granted Patent US 10,375,947
Granted Patent B2
US 10,375,947 · App. 15/787,182 · Granted Aug 13, 2019

Insect sensing systems and methods

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Quick Facts
Patent No.
US 10,375,947
App. No.
15/787,182
Granted
Aug 13, 2019
Kind
B2
Abstract

One example insect sensing system includes a light emitter configured to emit light; a structured light generator positioned to receive the emitted light and configured to generate structured light from the emitted light; a plurality of light sensors arranged in a line, each of the light sensors oriented to receive at least a portion of the structured light and output a sensor signal indicating an amount of light received by the respective light sensor; a processing device configured to: obtain the sensor signals from each of the light sensors, and determine a presence of an insect based a received sensor signal from at least one light sensor, the sensor signal indicating a reduced amount of received light by the at least one light sensor. Another example insect sensing system includes a camera comprising an image sensor and a lens having an aperture of f/2.8 or wider; and a processor configured to obtain an image from the camera and detect an insect in the image.

Claims (43)

1. A sensing system comprising:

a camera comprising an image sensor and a lens, the camera positioned to capture an image including an interior portion of an insect release tube, the camera oriented along a focal axis at an oblique angle to a longitudinal axis of the insect release tube, and a depth of focus of the camera is located within an interior volume of the insect release tube; and

a processor in communication with a non-transitory computer-readable medium and configured to execute processor-executable code stored in the non-transitory computer-readable medium to:

obtain an image from the camera;

identify at least one in-focus moving insect in the image; and

ignore any out-of-focus moving insect in the image.

2. The sensing system of claim 1 , wherein the processor is configured to execute processor-executable code stored in the non-transitory computer-readable medium to detect the in-focus moving insect in the image using an edge detection technique.

3. The sensing system of claim 2 , wherein the processor is configured to execute processor-executable code stored in the non-transitory computer-readable medium to:

generate an edge gradient map of the image, and

detect the at least one in-focus moving insect in the image using the edge gradient map.

4. The sensing system of claim 3 , wherein the processor configured to execute processor-executable code stored in the non-transitory computer-readable medium to:

for each pixel in the image, determine an edge using pixels within a pixel window centered on the respective pixel, and

generate the edge gradient map using the determined edges.

5. The sensing system of claim 1 , wherein the processor is configured to execute processor-executable code stored in the non-transitory computer-readable medium to detect the insect in the image using a machine learning technique.

6. The sensing system of claim 1 , wherein the processor is configured to execute processor-executable code stored in the non-transitory computer-readable medium to:

obtain multiple successive images from the camera and detect moving insects in the successive images at a rate of sufficient to capture multiple in-focus images of one or more moving insects, the rate based on the depth of focus and an average flight speed of a type of insects in an insect population to traverse the release tube.

7. The sensing system of claim 6 , wherein the processor is configured to execute processor-executable code stored in the non-transitory computer-readable medium to:

identify the in-focus moving insect in multiple consecutive images; and

increment an insect count by one for the identified in-focus moving insect in on image of the multiple consecutive images, and

not increment the insect count for the identified in-focus moving insect in the other images of the multiple consecutive images.

8. A method comprising:

obtaining an image from a camera comprising an image sensor and a lens;

identifying at least one in-focus moving insect in the image; and

ignoring any out-of-focus moving insect in the image; wherein:

the camera is positioned to capture images of an interior volume of an insect release tube,

the camera is oriented such that a focal axis of the camera is oriented at an oblique angle to a longitudinal axis of the release tube, and

a depth of focus of the camera is located within the interior volume of the insect release tube.

9. The method of claim 8 , further comprising:

iteratively obtaining images from the camera over a period of time;

detecting in-focus moving insects in the images; and

counting a number of detected in-focus moving insects over the period of time.

10. The method of claim 8 , further comprising:

generating an edge gradient map of the image, and

detecting the in-focus moving insect in the image using the edge gradient map.

11. The method of claim 8 , further comprising:

for each pixel in the image, determining an edge using pixels within a pixel window centered on the respective pixel, and

generating an edge gradient map using the determined edges, and wherein detecting the in-focus moving insect is based on the edge gradient map.

12. The system of claim 1 wherein the processor is configured to execute processor-executable code stored in the non-transitory computer-readable medium to:

obtain multiple images from the camera, the multiple images taken in succession over a period of time; and

identify moving insects within the images;

identify one or more in-focus insects in at least one of the images based on the identified moving insects;

detect at least one moving insect in the image based on the identified in-focus insects; and

ignore one or more out-of-focus insects within the images.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 2, 2026
From: VERILY LIFE SCIENCES LLC
To: GOOGLE LLC
Reel/Frame 074612/0400 →
CHANGE OF ADDRESS Recorded Nov 19, 2024
From: VERILY LIFE SCIENCES LLC
To: VERILY LIFE SCIENCES LLC
Reel/Frame 069390/0656 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 5, 2017
From: LIU, JIANYI; MASSARO, PETER
To: VERILY LIFE SCIENCES LLC
Reel/Frame 044297/0668 →
Cited By (3)
US 12,433,211 US 12,458,000 US 12,717,061