Symbol recognition from raster images of PandIDs using a single instance per symbol class

    公开(公告)号:US12039641B2

    公开(公告)日:2024-07-16

    申请号:US17722527

    申请日:2022-04-18

    摘要: Traditional systems that enable extracting information from Piping and Instrumentation Diagrams (P&IDs) lack accuracy due to existing noise in the images or require a significant volume of annotated symbols for training if deep learning models that provide good accuracy are utilized. Conventional few-shot/one-shot learning approaches require a significant number of training tasks for meta-training prior. The present disclosure provides a method and system that utilizes the one-shot learning approach that enables symbol recognition using a single instance per symbol class which is represented as a graph with points (pixels) sampled along the boundaries of different symbols present in the P&ID and subsequently, utilizes a Graph Convolutional Neural Network (GCNN) or a GCNN appended to a Convolutional Neural Network (CNN) for symbol classification. Accordingly, given a clean symbol image for each symbol class, all instances of the symbol class may be recognized from noisy and crowded P&IDs.

    Generating and processing an image property pixel structure

    公开(公告)号:US12131435B2

    公开(公告)日:2024-10-29

    申请号:US17424909

    申请日:2020-01-16

    摘要: The invention relates to an apparatus for generating or processing an image signal. A first image property pixel structure is a two-dimensional non-rectangular pixel structure representing a surface of a view sphere for the viewpoint. A second image property pixel structure is a two-dimensional rectangular pixel structure and is generated by a processor (305) to have a central region derived from a central region of the first image property pixel structure and at least a first corner region derived from a first border region of the first image property pixel structure. The first border region is a region proximal to one of an upper border and a lower border of the first image property pixel structure. The image signal is generated to include the second image property pixel structure and the image signal may be processed by a receiver to recover the first image property pixel structure.