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Natural immune system offers several fascinating options that motivated the planning of Artificial Immune Systems (AIS) accustomed solve varied issues of engineering and Artificial Intelligence (AI). AIS are significantly thriving in fault detection and diagnosing applications where anomalies like errors and failures are assimilated to viruses that ought to be detected. Thereby, AIS appear appropriate to automatically discover forgeries in signature verification systems. This work proposes a technique for offline signature verification that's supports the artificial Immune Recognition System (AIRS) and Artificial Neural Network (ANN) utilized in verification stage. For feature generation, two totally different descriptors are projected to get signature traits. the primary is that the Gaussian pyramid used for texture synthesis that is very redundant, coarse scales offer a lot of the data within the finer scales and Laplacian pyramid Seamlessly stitch along images into an image plaid (i.e., register the photographs and blurring the boundary), by smoothing the boundary in a very scale-dependent style to avoid boundary artefacts.

Offline Handwritten Signature Verification Method: Based on Artificial Immune Recognition System and Artificial Neural Network