  Printed Circuit Boards are the foundation for the functioning of any
electronic device, and therefore are an essential component for various
industries such as automobile, communication, computation, etc. However, one of
the challenges faced by the PCB manufacturers in the process of manufacturing
of the PCBs is the faulty placement of its components including missing
components. In the present scenario the infrastructure required to ensure
adequate quality of the PCB requires a lot of time and effort. The authors
present a novel solution for detecting missing components and classifying them
in a resourceful manner. The presented algorithm focuses on pixel theory and
object detection, which has been used in combination to optimize the results
from the given dataset.
