Automated Coin Recognition System using ANN

Abstract

Coins are integral part of our day to day life. We use coins everywhere like grocery store, banks, buses, trains etc. So it becomes a basic need that coins can be sorted and counted automatically. For this it is necessary that coins can be recognized automatically. In this paper we have developed an ANN (Artificial Neural Network) based Automated Coin Recognition System for the recognition of Indian Coins of denomination `1, `2, `5 and `10 with rotation invariance. We have taken images from both sides of coin. So this system is capable of recognizing coins from both sides. Features are extracted from images using techniques of Hough Transformation, Pattern Averaging etc. Then, the extracted features are passed as input to a trained Neural Network. 97.74% recognition rate has been achieved during the experiments i.e. only 2.26% miss recognition, which is quite encouraging.

Speed Limit Road Sign Detection and Recognition System

“…This is accomplished by generating a binary image includes the speed limit sign [9]. Logical AND operation was used to implement image segmentation algorithm taking three color space values; red, green and blue in RGB space and hue, saturation, and value in HSV space, and values of each of Y, Cr, and Cb in YCrCb space.…”

“…This method [9,16] was used to recognize speed limit signs numbers where a data base includes 2909 images of speed limit sign has been adopted to train the network and testing its achievement. The neural network was designed, trained and tested to recognize 8 types of speed limit (20, 30, 50, 60, 70, 80, 100, and 120).…”

Classification of Ancient Coin using Artificial Neural Network

“…By using segmentation, enhancement, consistency and coherent an object of the image can be identified. [5] The surface, illumination of the coin and the background of the image plays a major role to identify the coin. [9] The coin can be identifying at first by segmenting the image and then by fusing the local features and the border of the image.…”

Investigation of Dirty Area Recognition for Coin

“…Distinguishing processing is achieved based on the surface pattern of coins detected by image processing technology by Zhang Chi etc [15]. Coins are identified based on characteristic parameters of rotation invariance of coin image combining neural networks and genetic algorithms abroad [16][17][18][19].…”