Malaysia is an agriculture based country, which 70% of population depends on agriculture. There are need for ability to find and identify different kind of agriculture plants and herbs effectively for the purpose of finding and collecting. The identification of herbs plantation currently is ineffective and inefficient through manual process by trained human resources. This manual process of identifying useful herbs causes ineffective collecting and identifying of the natural resources. The manual approach involves expert human being based on leaves recognition. For huge area a researcher or expert required to cover a huge searching area which causes a lot of time and energy. The propose embedded system for identifying herbs through leaves recognition or what is called as A Low Cost Embedded System for Portable Herb Leaves Recognition System "" developed using concept of Image Processing Techniques and Neural Network Algorithms will ease the searching and identifying useful herb plants. This product describes techniques applied for hardware and software design of the devices. It involves edge detection, template matching and back propagation neural network to provide reasonable accuracy and speed.
This is the only product of this kind which implements image processing techniques and neural network algorithms using low cost embedded system design platform. This device enables leaves to be classified plants type. The plants type defined by it scientifically use for medical purposes. Biological data are obtained using Leaf Area Index (LAI) for the identification of the useful plant. The numbers of expertise in recognizing range of leaves are scarce. The needs of experts are required in order to find and identify leafs for collecting useful herbs for medical purposes. The numbers of herbs (which can be identifying by the unique pattern of leaves) are huge and it is impossible to provide enough people to perform the tasks. With the help of this device the finding and collecting herbs can be made more effectively and efficiently and also helps us to generate more expertise in recognizing range of herb leaves.