Processing apparatus, processing method, and computer readable medium

A processing apparatus comprising:

• at least one memory storing instructions, and
• at least one processor configured to execute the instructions to;
• classify three-dimensional point group data acquired based on a reflected light from a structure to be inspected illuminated by light into clusters, which are units of a shape that corresponds to the structure, based on positional information at each point of the data;
• determine whether a first cluster and a second cluster included in the classified clusters correspond to one structure based on a positional relation between the classified clusters;
• generate a first projection cluster obtained by projecting the first cluster onto a predetermined first plane and a second projection cluster obtained by projecting the second cluster onto the first plane;
• detect, for each of all the clusters classified, the longest direction in which the largest number of points are aligned, the first plane is-being vertical to the longest direction;
• and
• take into account a result of a determination regarding whether the first projection cluster matches the second projection cluster in the association between the first cluster and the second cluster.

A processing apparatus comprising:

• at least one memory storing instructions, and
• at least one processor configured to execute the instructions to;
• classify three-dimensional point group data acquired based on a reflected light from a structure to be inspected illuminated by light into clusters, which are units of a shape that corresponds to the structure, based on positional information at each point of the data;
• determine whether a first cluster and a second cluster included in the classified clusters correspond to one structure based on a positional relation between the classified clusters;
• detect, for each of all the clusters classified, the shortest direction in which the least number of points being aligned;
• calculate one of the angles between the shortest direction detected by the first cluster and the shortest direction detected by the second cluster that is smaller than the other one;
• calculate the difference between a first average distance, which is the average of distances between respective points included in the first cluster and a second plane, and a second average distance, which is the average of distances between respective points included in the second cluster and the second plane, the second plane being a plane vertical to the shortest direction detected by the first cluster;
• and
• take into account the angle and the difference in the association between the first cluster and the second cluster.

A processing apparatus comprising:

• at least one memory storing instructions, and
• at least one processor configured to execute the instructions to;
• classify three-dimensional point group data acquired based on a reflected light from a structure to be inspected illuminated by light into clusters, which are units of a shape that corresponds to the structure, based on positional information at each point of the data;
• determine whether a first cluster and a second cluster included in the classified clusters correspond to one structure based on a positional relation between the classified clusters;
• and
• determine whether there is a third cluster including points whose number is equal to or larger than a predetermined number in a position in front of a structure to be inspected between the first cluster and the second cluster with respect to a three-dimensional sensor that irradiates light on the structure to be inspected, and dissociate the first cluster with the second cluster when there is no third cluster, and associate the first cluster with the second cluster when there is the third cluster.

A processing apparatus comprising:

• at least one memory storing instructions, and
• at least one processor configured to execute the instructions to;
• classify three-dimensional point group data acquired based on a reflected light from a structure to be inspected illuminated by light into clusters, which are units of a shape that corresponds to the structure, based on positional information at each point of the data;
• determine whether a first cluster and a second cluster included in the classified clusters correspond to one structure based on a positional relation between the classified clusters,
• generate a distance image from point group data and calculate the average of pixel values of pixels included in a region between the first cluster and the second cluster in the distance image that has been generated;
• and
• dissociate the first cluster with the second cluster when the average is larger than a predetermined threshold and associate the first cluster with the second cluster when the average is below the predetermined threshold.

A processing method comprising:

• classifying three-dimensional point group data acquired based on a reflected light from a structure to be inspected illuminated by light into clusters, which are units of a shape that corresponds to the structure, based on positional information at each point of the data;
• determining whether a first cluster and a second cluster included in the classified clusters correspond to one structure based on a positional relation between the classified clusters;
• generating a first projection cluster obtained by projecting the first cluster onto a predetermined first plane and a second projection cluster obtained by projecting the second cluster onto the first plane, the first plane being vertical to a line that connects the center of gravity of the first cluster to the center of gravity of the second cluster;
• and
• taking into account a result of a determination regarding whether the first projection cluster matches the second projection cluster in the association between the first cluster and the second cluster.

A non-transitory computer readable medium storing a program for causing a computer to execute:

• classifying three-dimensional point group data acquired based on a reflected light from a structure to be inspected illuminated by light into clusters, which are units of a shape that corresponds to the structure, based on positional information at each point of the data;
• determining whether a first cluster and a second cluster included in the classified clusters correspond to one structure based on a positional relation between the classified clusters;
• generating a first projection cluster obtained by projecting the first cluster onto a predetermined first plane and a second projection cluster obtained by projecting the second cluster onto the first plane, the first plane being vertical to a line that connects the center of gravity of the first cluster to the center of gravity of the second cluster;
• and
• taking into account a result of a determination regarding whether the first projection cluster matches the second projection cluster in the association between the first cluster and the second cluster.

A processing method comprising:

• classifying three-dimensional point group data acquired based on a reflected light from a structure to be inspected illuminated by light into clusters, which are units of a shape that corresponds to the structure, based on positional information at each point of the data;
• determining whether a first cluster and a second cluster included in the classified clusters correspond to one structure based on a positional relation between the classified clusters;
• generating a first projection cluster obtained by projecting the first cluster onto a predetermined first plane and a second projection cluster obtained by projecting the second cluster onto the first plane;
• detecting, for each of all the clusters classified, the longest direction in which the largest number of points are aligned, the first plane being vertical to the longest direction;
• and
• taking into account a result of a determination regarding whether the first projection cluster matches the second projection cluster in the association between the first cluster and the second cluster.

A processing method comprising:

• classifying three-dimensional point group data acquired based on a reflected light from a structure to be inspected illuminated by light into clusters, which are units of a shape that corresponds to the structure, based on positional information at each point of the data;
• determining whether a first cluster and a second cluster included in the classified clusters correspond to one structure based on a positional relation between the classified clusters;
• detecting, for each of all the clusters classified, the shortest direction in which the least number of points being aligned;
• calculating one of the angles between the shortest direction detected by the first cluster and the shortest direction detected by the second cluster that is smaller than the other one;
• calculating the difference between a first average distance, which is the average of distances between respective points included in the first cluster and a second plane, and a second average distance, which is the average of distances between respective points included in the second cluster and the second plane, the second plane being a plane vertical to the shortest direction detected by the first cluster;
• and
• taking into account the angle and the difference in the association between the first cluster and the second cluster.

A processing method comprising:

• classifying three-dimensional point group data acquired based on a reflected light from a structure to be inspected illuminated by light into clusters, which are units of a shape that corresponds to the structure, based on positional information at each point of the data;
• determining whether a first cluster and a second cluster included in the classified clusters correspond to one structure based on a positional relation between the classified clusters;
• and
• determining whether there is a third cluster including points whose number is equal to or larger than a predetermined number in a position in front of a structure to be inspected between the first cluster and the second cluster with respect to a three-dimensional sensor that irradiates light on the structure to be inspected, dissociating the first cluster with the second cluster when there is no third cluster, and associating the first cluster with the second cluster when there is the third cluster.

A processing method comprising:

• classifying three-dimensional point group data acquired based on a reflected light from a structure to be inspected illuminated by light into clusters, which are units of a shape that corresponds to the structure, based on positional information at each point of the data;
• determining whether a first cluster and a second cluster included in the classified clusters correspond to one structure based on a positional relation between the classified clusters;
• generating a distance image from point group data and calculating the average of pixel values of pixels included in a region between the first cluster and the second cluster in the distance image that has been generated;
• and
• dissociating the first cluster with the second cluster when the average is larger than a predetermined threshold and associating the first cluster with the second cluster when the average is below the predetermined threshold.

A non-transitory computer readable medium storing a program configured to cause a computer to execute:

• classifying three-dimensional point group data acquired based on a reflected light from a structure to be inspected illuminated by light into clusters, which are units of a shape that corresponds to the structure, based on positional information at each point of the data;
• and
• determining whether a first cluster and a second cluster included in the classified clusters correspond to one structure based on a positional relation between the classified clusters;
• generating a first projection cluster obtained by projecting the first cluster onto a predetermined first plane and a second projection cluster obtained by projecting the second cluster onto the first plane;
• detecting, for each of all the clusters classified, the longest direction in which the largest number of points are aligned, the first plane being vertical to the longest direction;
• and
• taking into account a result of a determination regarding whether the first projection cluster matches the second projection cluster in the association between the first cluster and the second cluster.

A non-transitory computer readable medium storing a program configured to cause a computer to execute:

• classifying three-dimensional point group data acquired based on a reflected light from a structure to be inspected illuminated by light into clusters, which are units of a shape that corresponds to the structure, based on positional information at each point of the data;
• and
• determining whether a first cluster and a second cluster included in the classified clusters correspond to one structure based on a positional relation between the classified clusters;
• detecting, for each of all the clusters classified, the shortest direction in which the least number of points being aligned;
• calculating one of the angles between the shortest direction detected by the first cluster and the shortest direction detected by the second cluster that is smaller than the other one;
• calculating the difference between a first average distance, which is the average of distances between respective points included in the first cluster and a second plane, and a second average distance, which is the average of distances between respective points included in the second cluster and the second plane, the second plane being a plane vertical to the shortest direction detected by the first cluster;
• and
• taking into account the angle and the difference in the association between the first cluster and the second cluster.

A non-transitory computer readable medium storing a program configured to cause a computer to execute:

• classifying three-dimensional point group data acquired based on a reflected light from a structure to be inspected illuminated by light into clusters, which are units of a shape that corresponds to the structure, based on positional information at each point of the data;
• determining whether a first cluster and a second cluster included in the classified clusters correspond to one structure based on a positional relation between the classified clusters;
• and
• determining whether there is a third cluster including points whose number is equal to or larger than a predetermined number in a position in front of a structure to be inspected between the first cluster and the second cluster with respect to a three-dimensional sensor that irradiates light on the structure to be inspected, dissociating the first cluster with the second cluster when there is no third cluster, and associating the first cluster with the second cluster when there is the third cluster.

A non-transitory computer readable medium storing a program configured to cause a computer to execute:

• classifying three-dimensional point group data acquired based on a reflected light from a structure to be inspected illuminated by light into clusters, which are units of a shape that corresponds to the structure, based on positional information at each point of the data;
• determining whether a first cluster and a second cluster included in the classified clusters correspond to one structure based on a positional relation between the classified clusters;
• generating a distance image from point group data and calculating the average of pixel values of pixels included in a region between the first cluster and the second cluster in the distance image that has been generated;
• and
• dissociating the first cluster with the second cluster when the average is larger than a predetermined threshold and associating the first cluster with the second cluster when the average is below the predetermined threshold.