Object imaging and detection systems and methods
AssigneeDrilldocs Company
InventorsFrancois Ruel, Martin E. Oehlbeck, Deep Rajendrakumar Joshi, Calvin Stuart Holt
Life of this patent
Estimating the term…
Abstract
A method including selecting image data of a mechanical mud separation machines (“MMSM”) to detect objects in an object flow and other operational conditions at the MMSM. The image data may be processed by a Deep Neural Network to identify objects in the object flow, operational parameters of the MMSM, and environmental conditions. Additional image data may be selected for additional processing based on the results of the analysis.
Claims21
A computer-implemented method comprising:
- receiving image data from at least one imaging device imaging at least one mechanical mud separation machine (“MMSM”);
- selecting, from the image data, at least one Region of Interest (“ROI”);
- analyzing, using a Deep Neural Network (“DNN”), the at least one ROI to identify at least one image aspect in the ROI, wherein the image aspect is at least one of an object in an object flow, signal noise, or another physical object;
- based on results from the analyzing operation, selecting at least one additional ROIs from the image data;
- and
- analyzing the at least one additional ROIs using the DNN.
8-20. (canceled)
A system comprising at least one computer processor in electronic communication with at least one computer readable storage device storing instructions that, when executed, performs a method, the method comprising:
- receiving image data from at least one imaging device imaging at least one mechanical mud separation machine (“MMSM”);
- selecting, from the image data, at least one Region of Interest (“ROI”);
- analyzing, using a Deep Neural Network (“DNN”), the at least one ROI to identify at least one image aspect in the ROI, wherein the image aspect is at least one of an object in an object flow, signal noise, or another physical object;
- based on results from the analyzing operation, selecting at least one additional ROIs from the image data;
- and
- analyzing the at least one additional ROIs using the DNN.
A computer readable storage device storing instructions that, when executed, performs a method, the method comprising:
- receiving image data from at least one imaging device imaging at least one mechanical mud separation machine (“MMSM”);
- selecting, from the image data, at least one Region of Interest (“ROI”);
- analyzing, using a Deep Neural Network (“DNN”), the at least one ROI to identify at least one image aspect in the ROI, wherein the image aspect is at least one of an object in an object flow, signal noise, or another physical object;
- based on results from the analyzing operation, selecting at least one additional ROIs from the image data;
- and
- analyzing the at least one additional ROIs using the DNN.
Dependencies are inferred from the claim text.