IP Library Granted Patent US 11,094,055
Granted Patent B2
US 11,094,055 · App. 16/245,758 · Granted Aug 17, 2021

Anomaly detection system

Inventors: Ara Victor Nefian (San Francisco, CA); Hrant Khachatryan (Yerevan, AM); Hovnatan Karapetyan (Yerevan, AM); Naira Hovakymian (Champaign, IL)
Assignee: Intelinair, Inc.
G06T7/001G06K9/00657G06K9/6212G06T5/002G06T5/20G06T5/50G06T7/0002G06T7/0012G06T7/10G06T7/11G06T7/136G06T7/74G06T2207/10024G06T2207/10032G06T2207/20021G06T2207/30188
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Quick Facts
Patent No.
US 11,094,055
App. No.
16/245,758
Granted
Aug 17, 2021
Kind
B2
Abstract

An image analysis system including an image gathering unit that gathers a high-altitude image having multiple channels, an image analysis unit that segments the high-altitude image into a plurality of equally size tiles and determines an index value based on at least one channel of the image where the image analysis unit identifies areas containing anomalies in each image.

Claims (29)

1. An image analysis system including:

an image capture unit that captures at least one a high-altitude image having multiple channels;

an image analysis unit operating in the memory of a computer that segments the high-altitude image into a plurality of tiles with each tile having a same pixel width and a same pixel height as an adjacent tile and determines an index value based on at least one channel of the image,

wherein the image analysis unit identifies areas containing anomalies in each image by analyzing areas connected to identified anomalies to determine areas where anomalies exist, and

a score is assigned to each identified anomaly and an anomaly rectangle is placed on the image to identify areas where anomalies are identified.

2. The image analysis system of claim 1 , wherein the index determined is a normal differential vegetation index for a segment of the captured image.

3. The image analysis system of claim 1 , wherein the index determined is a soil adjusted vegetation index for a segment of the captured image.

4. The image analysis system of claim 1 , wherein the image analysis unit masks the segment of the image using a confidence mask based on the index value.

5. The image analysis system of claim 4 , wherein the image analysis unit normalizes the masked segment of the image.

6. The image analysis system of claim 5 , wherein the image analysis unit calculates a mean and standard deviation of the segment of the normalized image.

7. The image analysis system of claim 6 , wherein the image analysis unit applies a box averaging threshold to the segment of the normalized image.

8. The image analysis system of claim 7 wherein the image analysis unit calculates a mean for each pixel in the applied box.

9. The image analysis system of claim 8 , wherein the image analysis unit removes pixels from the segment of the image that have a calculated mean below a predetermined threshold.

10. The image analysis system of claim 9 , wherein the image analysis unit calculates a score for each of the remaining pixels and draws a rectangle around groups of pixels based on the scores of each pixel.

11. An image analysis unit including a processor and a memory with a method of analyzing an image performed in the memory, the method including the steps of:

gathering a high-altitude image having multiple channels via an image capture unit;

segmenting the high-altitude image into a plurality of tiles with each tile having a same pixel width and a same pixel height as an adjacent tile via an image analysis unit;

determining an index value based on at least one channel of the image via the image analysis unit;

identifying areas containing anomalies in each image via the image analysis unit identifies areas containing anomalies in each image by analyzing areas connected to identified anomalies to determine areas where anomalies exist, and

assigning a score to each identified anomaly and placing an anomaly rectangle on the image to identify areas where anomalies are identified.

12. The method of claim 11 , wherein the index determined is a normal differential vegetation index for a segment of the captured image.

13. The image analysis system of claim 11 , wherein the index determined is a soil adjusted vegetation index for a segment of the captured image.

14. The image analysis system of claim 11 , wherein the step of identifying anomalies includes masking the segment of the image using a confidence mask based on the index value.

15. The image analysis system of claim 14 , wherein the step of identifying anomalies includes normalizing the masked segment of the image.

16. The image analysis system of claim 15 , wherein the step of identifying anomalies includes calculating a mean and standard deviation of the segment of the normalized image.

17. The image analysis system of claim 16 , wherein the step of identifying anomalies includes applying a box averaging threshold to the segment of the normalized image.

18. The image analysis system of claim 17 wherein the step of identifying anomalies includes calculating a mean for each pixel in the applied box.

19. The image analysis system of claim 18 , wherein the step of identifying anomalies includes removing pixels from the segment of the image that have a calculated mean below a predetermined threshold.

20. The image analysis system of claim 19 , wherein the step of identifying anomalies includes calculating a score for each of the remaining pixels and drawing a rectangle around groups of pixels based on the scores of each pixel.

Assignments (1)
SECURITY INTEREST Recorded Mar 9, 2022
From: INTELINAIR, INC.
To: MCKINSEY & COMPANY, INC. UNITED STATES
Reel/Frame 059206/0843 →
Continuity (2)
Provisional Application 62616159 · Jan 11, 2018
Related Publication 20190213727A1 · Jul 11, 2019
Cited By (1)
US 12,293,511