Skip to content Skip to navigation Skip to collection information

OpenStax-CNX

You are here: Home » Content » ELEC 301 Projects Fall 2006 » Pocket Change: Introduction and Background

Navigation

Table of Contents

Lenses

What is a lens?

Definition of a lens

Lenses

A lens is a custom view of the content in the repository. You can think of it as a fancy kind of list that will let you see content through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

This content is ...

Affiliated with (What does "Affiliated with" mean?)

This content is either by members of the organizations listed or about topics related to the organizations listed. Click each link to see a list of all content affiliated with the organization.
  • Rice University ELEC 301 Projects

    This collection is included inLens: Rice University ELEC 301 Project Lens
    By: Rice University ELEC 301

    Click the "Rice University ELEC 301 Projects" link to see all content affiliated with them.

  • Rice Digital Scholarship

    This collection is included in aLens by: Digital Scholarship at Rice University

    Click the "Rice Digital Scholarship" link to see all content affiliated with them.

Also in these lenses

  • Lens for Engineering

    This collection is included inLens: Lens for Engineering
    By: Sidney Burrus

    Click the "Lens for Engineering" link to see all content selected in this lens.

Recently Viewed

This feature requires Javascript to be enabled.
 

Pocket Change: Introduction and Background

Module by: Tyler J.W. Barth, Aaron D. Cottle, John P. Stallcup, Christopher J. Vaucher. E-mail the authors

Summary: An introduction the Rice University ELEC 301 Fall 2006 coin recognition project.

Introduction

Many tedious processes can be automated using computers. Counting and sorting objects, especially in large numbers, is an area where humans are simply less efficient. Applying this knowledge to the problem of identifying and counting coins, a software system can be developed to recognize and tally a handful of change. The following modules describe the challenges associated with building a system that accomplishes these tasks. Good luck on your journey!

Background

Object recognition and identification are important aspects of machine vision. Coin recognition in particular poses a special challenge for two reasons: 1. Coins are notoriously difficult to photograph. They are reflective, and there are trade-offs in evenness of lighting vs. visibility of details when determining lighting. 2. Coins are circular objects. Unlike playing cards, where long edges can be determined and the original image can be transformed to a standard angle from which comparisons can be made, coins can have arbitrary orientations and there is no way to determine them without knowing the identity of the coin.

Process Overview

There is a systematic process that the machine must follow to determine the identity of a coin. The rest of this course will go into greater detail in each step.

Image Acquisition

First, an image must be acquired. You might imagine that this part of the process would be the simplest, but it actually ended up being one of our steps that was most fraught with difficulties. Lighting ends up becoming a big issue, leading to misidentification in systems with uneven lighting and necessitating the use of diffuse light sources.

Circle Recognition

Once the image is in the computer, the first step is to locate the coins in the scene. This can be accomplished using off-the-shelf code that implements a feature extraction technique known as the Circular Hough Transform. Feeding the function the image and a range of radii to detect, it will, with high accuracy, return the radius and center of every circle (coin, in this case) in that range in the picture.

Coin FFT Creation

Radius and center data in hand, now we get to the meat of the project: recognizing the coins. The key difficulty in recognizing coins is their very circular nature. As mentioned previously, they can have any phase. Normally you might use a matched filter to try to determine identity of an object (the filter with the greatest resulting magnitude is the filter of the coin). If you were going to do that in this case, you would need a separate matched filter not only for each coin surface, but for each coin surface at every possible rotation. We take a different approach. Exploiting the properties of Fourier transforms and going through an “unwrapping process”, we are able to create unique FFTs that are orientation agnostic.

Coin Identification

Once we have the FFT of the coin, we have to determine which coin it is. Beforehand, we create a database of FFTs of known coins we want to recognize. Then, using one of many possible comparison algorithms, we compare the FFT of the current coin to each coin in the database, selecting the comparison with the closest match as the identity of the coin.

Output Display

Once the information about each coin is known, we can display it in any way we want. Because we record lots of metadata for each coin, in addition to the sum we can display all sorts of interesting statistics about the coins in the image. We also created a way to allow rapid error checking by superimposing the values of the coins onto the image of the coins.

Figure 1: This is a pictorial representation of the process described above.
Flow chart
Flow chart (flow.png)

Collection Navigation

Content actions

Download:

Collection as:

PDF | EPUB (?)

What is an EPUB file?

EPUB is an electronic book format that can be read on a variety of mobile devices.

Downloading to a reading device

For detailed instructions on how to download this content's EPUB to your specific device, click the "(?)" link.

| More downloads ...

Module as:

PDF | More downloads ...

Add:

Collection to:

My Favorites (?)

'My Favorites' is a special kind of lens which you can use to bookmark modules and collections. 'My Favorites' can only be seen by you, and collections saved in 'My Favorites' can remember the last module you were on. You need an account to use 'My Favorites'.

| A lens I own (?)

Definition of a lens

Lenses

A lens is a custom view of the content in the repository. You can think of it as a fancy kind of list that will let you see content through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

| External bookmarks

Module to:

My Favorites (?)

'My Favorites' is a special kind of lens which you can use to bookmark modules and collections. 'My Favorites' can only be seen by you, and collections saved in 'My Favorites' can remember the last module you were on. You need an account to use 'My Favorites'.

| A lens I own (?)

Definition of a lens

Lenses

A lens is a custom view of the content in the repository. You can think of it as a fancy kind of list that will let you see content through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

| External bookmarks