The current system can only identify eight different fruits or
vegetable at one possible time. To increase the number of fruits
identified the features extracted should be more and relationship
between these features need to be created. One way of achieving this is
through genetic algorithm and learning techniques that would enable
it to learn a particular fruit. Another technique that can be used is an
electronic nose as a sensory input. This would greatly reduce the need
to extract further features as every fruit and vegetable expels different
chemicals and hence can be used for the identification of the fruit
and this also reduces the storage space for the processing the features.
Combining these two parameters of we can develop a near foolproof
fruit sorting or vegetable sorting system.