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Out of every 135,000 used tires purchased, only 8,000 make it to the final stage to be made reusable [1]. The cost for purchasing, handling, transporting as well as inspection by experts results in heavy losses accrued which demotivates both individuals as well as organisations from adopting such recycling strategies. Here we propose a solution which will help reduce the cost as well make the process efficient and time saving. For identifying reusable truck tires effectively and prevent discarding of completely fine tires, deep learning is used to realise the image recognition of good and scrap truck tires. Firstly, Shearography Tire testing is done in the production laboratory or on the test track. Vacuum chamber measuring system helps- in taking multiple pictures of tires. Then image enhancement and data preprocessing are used to augment images, then these were input into the network for training.