Ayurvedic Herb Detection using Image Processing
Trees are an inseparable part of our ecosystem and the reducing number of herb varieties is a serious problem. To conserve herbs, their immediate identification by botanists is a must, thus a tool is needed which could identify herbs using easily accessible details. There is a growing scientific consensus that plant shelters have been altered and species are dying at rates never seen before. The biodiversity problem is not just about the problematic state of herbs species but also of the specialists who know them. This initially requires data about various plant species, so that they could be foreseen, protected and can be used for next generation. Plants form the basis of Ayurveda and today s Modern day medicine are a great source of income. Due to cutting of forests and Pollution, lot of medicinal herb leaves have almost become extinct. So, there is an immediate need for us to identify them and replant them for the use of next generations. Leaf Identification by physical means often leads to incorrect identification. Due to increasing illegal transaction and incorrect practices in the nascent drug industry on one hand and lack of enough professionals on the other hand, a self automated and robust identification and classification mechanism is needed to manage the huge amount of data and to end the malpractices. This paper aims at implementing such system using image processing with images of the plant leaves as a basis of classification. System returns the closest match to the query. The proposed algorithm is implemented on 5 different plant species.
Gaussian blur, shape features, colour features, contour, thresholding, perspective transformation
Dinesh Shitole | Faisal Tamboli | Krishna Motghare | Raj Kumar Raj