This project focuses on the identification of colon cancer using a publicly available dataset of histopathology images of colon cancer. 4 models are proposed based on image processing for identifying colon cancer. We employed deep learning based Keras Sequential CNN model, VGG16 based model, ResNet50 V2 based model and EffecientNet model to identify the best model for classifying colon cancer.In this research, data filtering, data enhancement, data segmentation, data augmentation, and layer modification techniques are used. We used 2 classes (colon adenocarcinoma, colon benign tissue) to develop model.. Finally, after segmentation among 4 models EffecientNet model gives the best training accuracy of 81.25% and validation accuracy of 80.21%.