Almost all over the world, the economy mainly depends on the production of food. Computer vision technology plays a pivotal role in the field of agriculture. The dream of this research is to produce successful crops in the agricultural sector. Successful farming can increase crop production in terms of both quality and quantity. The farming performs eight major phases which begin from crop selection to harvesting. At any of these phases, the disease and pest may destroy plants. However, the leaves are found to be the most damaged part in disease identification. A lot of articles are taken out for the survey that endorses the mechanism of image processing and deep learning for the detection and classification of diseases from the crop leaves. This survey provides an overview of the pros and cons of all such articles on various research aspects. The effectiveness of state-of-the-art methods is explored to identify the techniques that seem to work well across different crops. This paper indicates that algorithms like Support Vector Machine and Neural Network play an important role in the crop disease identification and classification.