Abstract: An information processing apparatus comprises: acquiring a first image including at least a part of an inspection device and a second image including at least a part of a subject; estimating a position of the inspection device based on the first image; estimating position and orientation information for the subject based on the second image; identifying an inspection region of the subject from results of estimating; and receiving a finalization instruction to finalize an inspection result to be recorded or output to an external apparatus based on sequentially acquired inspection results of the subject, and a finalization instruction to finalize inspection region information to be recorded or output to the external apparatus in association with the inspection result, wherein the finalization instruction for the inspection region information is received before the finalization instruction for the inspection result.

Abstract: An information processing apparatus includes one or more processors and a memory storing instructions which cause the information processing apparatus to: acquire a first image including at least a portion of an inspection device, and a second image including at least a portion of a subject; predict, as a first prediction, a position of the inspection device based on the first image; predict, as a second prediction, position/orientation information regarding the subject based on the second image. The instructions cause the apparatus to identify an inspection part of the subject based on the first prediction and the second prediction. Based on a learning model trained in advance using a plurality of images, the second prediction is performed and a result of the second prediction is an output of the position/orientation information regarding the subject.

Abstract: An information processing apparatus comprises: acquiring a first image including at least a part of an inspection device and a second image including at least a part of a subject; estimating a position of the inspection device based on the first image; estimating position and orientation information for the subject based on the second image; identifying an inspection region of the subject from results of estimating; and receiving a finalization instruction to finalize an inspection result to be recorded or output to an external apparatus based on sequentially acquired inspection results of the subject, and a finalization instruction to finalize inspection region information to be recorded or output to the external apparatus in association with the inspection result, wherein the finalization instruction for the inspection region information is received before the finalization instruction for the inspection result.

Abstract: An image processing method can suppress detection accuracy of a detection target object from being lowered even if the detection target object has a different surface condition because of the influence of various kinds of noise. The image processing method includes the following operations of generating a captured model edge image by executing edge extraction processing on a captured model image acquired by capturing a detection target object, executing pattern matching of the captured model edge image and a model edge image, calculating similarity at respective edge points in the model edge image in the pattern matching of the captured model edge image and the model edge image, selecting an edge point to be eliminated based on the similarity from among the respective edge points in the model edge image, and generating an edge image acquired by eliminating the selected edge point as a final model edge image.

Abstract: A processor performs pattern matching on a search target image using a reference image. The processor uses the reference image to calculate a model pyramid, which has model edges and different layers, and uses the search target image to calculate the search target pyramid, which has search target edges and layers having size reduction factors which are the same as those of the model pyramid. The processor performs pattern matching on the search target pyramid using the model pyramid. Calculation of the model pyramid includes (i) extracting and calculating sizes of edges from the reference image, (ii) obtaining maximum size reduction factors of the individual edges, and (iii) setting an edge (a) which has a size reduction factor equal to or larger than a target layer size reduction factor and (b) which has been subjected to size reduction as a model edge of the target layer.

Abstract: A processor performs pattern matching on a search target image using a reference image. The processor uses the reference image to calculate a model pyramid, which has model edges and different layers, and uses the search target image to calculate the search target pyramid, which has search target edges and layers having size reduction factors which are the same as those of the model pyramid. The processor performs pattern matching on the search target pyramid using the model pyramid. Calculation of the model pyramid includes (i) extracting and calculating sizes of edges from the reference image, (ii) obtaining maximum size reduction factors of the individual edges, and (iii) setting an edge (a) which has a size reduction factor equal to or larger than a target layer size reduction factor and (b) which has been subjected to size reduction as a model edge of the target layer.

Abstract: An image processing method can suppress detection accuracy of a detection target object from being lowered even if the detection target object has a different surface condition because of the influence of various kinds of noise. The image processing method includes the following operations of generating a captured model edge image by executing edge extraction processing on a captured model image acquired by capturing a detection target object, executing pattern matching of the captured model edge image and a model edge image, calculating similarity at respective edge points in the model edge image in the pattern matching of the captured model edge image and the model edge image, selecting an edge point to be eliminated based on the similarity from among the respective edge points in the model edge image, and generating an edge image acquired by eliminating the selected edge point as a final model edge image.