Abstract

Abstract-- Flower is a very important part of nature. Mostly we identify a plant through its flower. Experienced botanists do this identification of flower but a naive person will have to consult flower guidebooks or browse any relevant web pages on the Internet through keywords searching. Our system can recognize the flower in real time using mobile camera. We are continuously working to add more flowers to identify. Every day, we see a huge number of flower species in our house, parks, roadsides, in farms, on our rooftop but we have no knowledge of that flower species or their origin. Even we have no idea about its name. There are several guidebooks for flowers knowledge but it becomes quite difficult to find the name when have the picture. Even the Internet sometimes is not useful. But it is quite difficult for human brain to memorize all the species they see. Even some flower is similar to look at. This application recognizes the flower in real time by using mobile camera. The purpose of this project is to use Tensor flow, an open-source dataflow and image processing, to build an image classifying Convolutional Neural Network (CNN) for classifying the flower image. Tensor flow, in addition to providing developers a simple way to buildneural network layers, can also be run on mobile platforms such as Android. The ultimate goal of this project is to design and optimize a convolutional neural network for use with flower classification, and eventually build a simple classification app for mobile devices around the trained network.Keywords: Flower recognition, flower detection, image processing, convolutional neural network