**5.2 Knowledge representation and knowledge learning**

**Figure 4** shows the block diagram of our proposed novel biologically-inspired hybrid digital-optical system called, Fast SDF K-means. It is a hybrid digital-optical design. Thus, the optical part and the K-means Clustering unit forms the digital part. The term "Fast" originates from the optical unit of the design where it consists of a correlator which can be implemented as a space domain function in a joint transform *A Cognitive Digital-Optical Architecture for Object Recognition Applications in Remote… DOI: http://dx.doi.org/10.5772/intechopen.109028*

**Figure 4.** *Fast SDF K-means classifier for endangered species speciation.*

correlator architecture or be Fourier Transformed (FT) and used as a Fourier domain filter in a 4-f Vander Lugt type optical correlator [26]. Therefore, it can operate to the speed of the light wavelength.

On **Figure 4** two different modules are shown. The first is the knowledge representation module [45, 46] which consists of the optical correlator unit, and the second is the knowledge learning module. In effect, in the first module of the knowledge representation the shape, size and 3-band colour information of each input image are synthesised into the composite image of the Fast SDF K-means Classifier. For each input object then a correlation peak value is recorded which translates this information into a numerical value. This essentially forms the knowledge representation of all the objects space in the training set.

In the second module of the knowledge learning [47], spectral histogram information together with the composite image which consists of shape, size and colour information are learned by the Fast SDF K-means Classifier. Thus, the correlation peak value together with the Red and Blue components of the spectral histogram form a 3D vector for each input object. Then, those 3D vectors which have coded the shape, size, colour and histogram information of each object are unsupervised learned by the K-means clustering unit. The output values of the Fast SDF K-means Classifier can be visualised by a scatter plot of the recognised endangered species 1 and 2 where the separate clusters of the two classes can be observed together shown with any input objects either from endangered species 1 class or from endangered species 2 class which have been misclassified.
