This paper presents the effects of pre-processed image based training data on Convolutional Neural Network’s (CNN’s) training accuracy where training dataset is small and insufficient. The goal of this research is to discover whether or not a convolutional neural network can perform better with a small quantity of image dataset that are pre-processed using color quantization through K-means clustering or histogram equalization.