A Smart Machine Vision based Inspection System

Abstract

Abstract: This article proposes a unique optimization like
Adaptive Cuckoo Search (AdCS) algorithm followed by an
Intrinsic Discriminant Analysis (IDA) to design a smart
intelligent object classifier for inspection of defective object like
bottle in a manufacturing unit. By using this methodology, the
response time is very faster than the other techniques. The
projected scheme is authenticated using different benchmark
test functions and in the next part of the article proposes an
efficient recognition algorithm for identification of bottle by
using AdCS, Principal Component Analysis (PCA) and IDA.
Due to this *the proposed algorithms terms as PCA+IDA for
dimension reduction *and AdCS-IDA for classification or
identification of defective bottles. The analyzed *response
obtained *from by an application of AdCS algorithm followed
by IDA and compared to other algorithm like Least-SquareSupport-Vector-Machine (LSSVM) along with Linear Kernel
Radial-Basis-Function (RBF) to the proposed model, the
earlier applied scheme reveals the remarkable performance
Index !Terms: Adaptive !Cuckoo !Search !(AdCS) algorithm,
Intrinsic Discriminant !Analysis !(IDA), !Principal Component
Analysis !(PCA), intelligent object classifier, least square
Support !Vector !Machine !(LSVM), Smart inspection.