Clinical Diagnosis of Parkinson’s disease [PD] leads to errors, excessive medical costs, and provide insufficient services to the patients. There is no particular method or a test to detect the PD. The diagnosis of the Parkinson’s disease needs an accurate detection. Computer Aided Diagnosis (CAD) gives accurate results to detect the PD. These CAD can be embedded into a real time application for the early diagnosis of PD. Dopamine nerve terminals can be reduced in the brain parts such as Substantia nigra, Striatum, and other brain structures. This reduction which will lead to Parkinson’s disease. Dopamine Reduction gets automatically diagnosed by CAD and PD/normal patients can be found. For this, machine learning system (MLS)/CAD can be trained with the help of Artificial Neural Networks (ANN). Image processing techniques that are available to detect PD using MLS/CAD gets discussed in this paper.