Our planet is blessed with various species of fauna and flora. It’s well known that plants play a crucial role in preserving the earth’s ecology and environment by maintaining a healthy atmosphere and providing sustenance and shelter to innumerable insect and animal species. Plants are also important for their medicinal properties and as alternative energy sources like bio-fuel. Today as many types of plants are at the brink of extinction. In our day to day life herbal plays vital role on human physic maintenance. Plant classification has a broad application perspective in agriculture medicine and is especially significant to the biology diversity research. In recent time’s computer vision have been successfully applied towards automated systems of plant cataloguing. The proposed system tries to bring atomization in the process of plant leaf classification such that without any precious knowledge of the leaf species, we are trying to detect the leaf. This will help the botanists in their study and speed up the process of identifying the species of plant. India is enriching source of plant species which is the base of ‘Ayurveda’ so the classification and identification of various plant species is one of the important phase. Our idea is to develop an automated tool which would detect and classify the plant leaf species after comparing with the trained sets. These trained sets are used by Artificial Neural Network (ANN) after image processing. The Neural Network would be trained for detection of edge and vein analysis. Earlier atomization was difficult, but now due to drastic development in technological field it is possible in just few steps. This paper proposes the automated tool for plant leaf recognition of leaf its digital image. Manual identification requires prior knowledge of species and is a lengthy process, thus the atomization technique helps to speed up the traditional method of plant leaf classification. Also the paper compares different methods used in plant leaf classification.