Method and system for tire tread pattern image segmentation
AssigneesThe Goodyear Tire & Rubber Company, Luxembourg Institute of Science and Technology
InventorsDuc Alexandre Fehr, Frank Petry, Uriel Rodrigo Nava Velazco
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Abstract
The invention provides a computer-implemented method and a system for automatically segmenting thermal images of a tire's footprint in order to identify components of the tire's tread pattern. The invention relies on a convolutional neural network model and on digital image pre-filtering. It is capable of accurately segmenting thermal footprint images of tires in either straight rolling or cornering conditions, which allows for the accurate extraction of temperature data for each identified tread pattern component.
Claims20
A computer-implemented method for identifying components of a tire's tread pattern in an input thermal footprint image of a tire acquired from underneath a surface that is transparent to infrared radiation, while the tire is rolling thereon, the method comprising the steps of
- providing a convolutional neural network model in a memory element, which is trained to identify the components of a tire's tread pattern in an input thermal footprint image of a tire;
- executing the convolutional neural network model to identify components of a tire's tread pattern in the input thermal footprint image of a tire, thereby generating a segmentation mask of the input thermal footprint image;
- wherein executing the convolutional neural network model comprises the steps of:
- associating a resolution value with each of a plurality of consecutive processing stages forming the convolutional neural network model, each processing stage comprising an encoder block and an associated decoder block;
- processing, at an encoder block of at least one processing stage, an encoder input having the resolution value associated with the processing stage, into an output having the same resolution value, which is forwarded to an associated decoder block, and which is down-sampled to a lower resolution value for processing by a processing stage associated with the lower resolution value;
- processing, at a decoder block of said at least one processing stage, a decoder input comprising a concatenation of the output forwarded by an associated encoder block and of an up-sampled output generated by a processing stage associated with a lower resolution value, into a processing stage output having the resolution value associated with the decoder block's processing stage;
- and wherein processing at the encoder block and at the decoder block comprises
- processing the respective input into a plurality of filtered intermediate outputs by using an atrous convolution step, wherein a filtering kernel is used at a corresponding plurality of different kernel dilution rates, and
- computing the respective output by generating an average of the filtered intermediate outputs.
A computer-implemented method for identifying components of a tire's tread pattern in an input thermal footprint video of a tire comprising a sequence of input thermal footprint images of a tire acquired from underneath a surface that is transparent to infrared radiation while the tire is rolling thereon, the method comprising the steps of
- providing a convolutional neural network model in a memory element, which is trained to identify the components of a tire's tread pattern in an input thermal footprint image of a tire;
- executing the convolutional neural network model to identify components of a tire's tread pattern in each input thermal footprint image of the input thermal footprint video of a tire, thereby generating a segmentation mask for each input thermal footprint image;
- wherein executing the convolutional neural network model comprises the steps of:
- associating a resolution value with each of a plurality of consecutive processing stages forming the convolutional neural network model, each processing stage comprising an encoder block and an associated decoder block;
- processing, at an encoder block of at least one processing stage, an encoder input having the resolution value associated with the processing stage, into an output having the same resolution value, which is forwarded to an associated decoder block, and which is down-sampled to a lower resolution value for processing by a processing stage associated with the lower resolution value;
- processing, at a decoder block of said at least one processing stage, a decoder input comprising a concatenation of the output forwarded by an associated encoder block and of an up-sampled output generated by a processing stage associated with a lower resolution value, into a processing stage output having the resolution value associated with the decoder block's processing stage;
- and wherein processing at the encoder block and at the decoder block comprises
- processing the respective input into a plurality of filtered intermediate outputs by using an atrous convolution step, wherein a filtering kernel is used at a corresponding plurality of different kernel dilution rates, and
- computing the respective output by generating an average of the filtered intermediate outputs.
A system for identifying components of a tire's tread pattern in an input thermal footprint image of a tire acquired from underneath surface that is transparent to infrared radiation, while the tire is rolling thereon, the system comprising
- a memory element holding a convolutional neural network model, which is trained to identify the components of a tire's tread pattern in an input thermal footprint image of a tire;
- a data processor configured to execute the convolutional neural network model to identify components of a tire's tread pattern in the input thermal footprint image of a tire, thereby generating a segmentation mask of the input thermal footprint image;
- wherein executing the convolutional neural network model comprises the steps of:
- associating a resolution value with each of a plurality of consecutive processing stages forming the convolutional neural network model, each processing stage comprising an encoder block and an associated decoder block;
- processing, at an encoder block of at least one processing stage, an encoder input having the resolution value associated with the processing stage, into an output having the same resolution value, which is forwarded to an associated decoder block, and which is down-sampled to a lower resolution value for processing by a processing stage associated with the lower resolution value;
- processing, at a decoder block of said at least one processing stage, a decoder input comprising a concatenation of the output forwarded by an associated encoder block and of an up-sampled output generated by a processing stage associated with a lower resolution value, into a processing stage output having the resolution value associated with the decoder block's processing stage;
- and wherein processing at the encoder block and at the decoder block comprises
- processing the respective input into a plurality of filtered intermediate outputs by using an atrous convolution step, wherein a filtering kernel is used at a corresponding plurality of different kernel dilution rates, and
- computing the respective output by generating an average of the filtered intermediate outputs.
Dependencies are inferred from the claim text.