attachment for aadhar authentication … for aadhar authentication on aakash image sharpening the...

WORKFLOW IMAGE CAPTURE The image is captured using the optical assembly, which works on the principle of FrustratedTotal Internal Reflection(FTIR). ATTACHMENT FOR AADHAR AUTHENTICATION ON AAKASH IMAGE SHARPENING The ridges of the image are enhanced using Laplacian kernel based convolution. Image after sharpening Histogram of image after sharpening FUTURE SCOPE • Increase the accuracy of optical assembly by testing with IR and SMD LEDs. • Expand the utility of the application to other devices. • Use a 35 mm lens (from disposable cameras) to increase the image quality to a great extent. ENHANCED BINARY IMAGE SENT TO SERVER The final enhanced image is sent to the Aadhar Authentication Service Agency which sends back the authentication result. PURPOSE • This application is developed primarily for capturing the user’s fingerprint using Aakash tablet. • The existing system uses an external scanner which increases the cost while the system developed by us uses an optical assembly which uses the Aakash tablet’s camera itself and hence is low cost. •The image captured using the tablet’s camera is later refined and delivered to Authentication Service Agency(ASA) server for the authentication of the Aadhar card holder. Captured image ADAPTIVE HISTOGRAM EQUALIZATION (AHE) This step is used to increase the contrast of the image by stretching the histogram. Image after AHE Histogram of image after AHE LIVE FINGER DETECTION It detects whether the finger is a spoof or not. It converts the RGB image to grayscale, and then considers the effect of perspiration on it. IMAGE THRESHOLDING The grayscale image is converted to its black and white image by using threshold values. Experimental threshold value : 172 Image after thresholding Histogram of image after thresholding IMAGE THINNING This step reduces the thickness of the ridges to help easily identify the minutiae. Image after thinning Histogram of image after thinning HARDWARE USED: • Black acrylic (3 mm thick) • Transparent acrylic (3 mm thick, 32.5mm x 35 mm) • PCB • LEDs (4 quantity, 3 mm thick) • Resistors (4 quantity, 220 ohms) • Power source 4.5V ( 3 AAA (1.5V) cells in series) • Switch Fundamental Research Group, Dept of CSE, IIT Bombay CONTRIBUTORS Prashant Main Sonu Philip Hitesh Yadav Pooja Deo Prathamesh Paleyekar Sudhanshu Verma Archana Iyer Prateek Somani Summer Internship 2013(9th May to 7th July) email: [email protected] Optical assembly Glass plate Clamp design by: Bhairav Aakash tablet Spacer

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Page 1: ATTACHMENT FOR AADHAR AUTHENTICATION … FOR AADHAR AUTHENTICATION ON AAKASH IMAGE SHARPENING The ridges of the image are enhanced using Laplacian kernel based convolution

WORKFLOW

IMAGE CAPTUREThe image is captured using the optical assembly, which works on the principle of Frustrated Total Internal Reflection(FTIR).

ATTACHMENT FOR AADHAR AUTHENTICATION ON AAKASH

IMAGE SHARPENINGThe ridges of the image are enhanced using Laplacian kernel based convolution.

Image after sharpeningHistogram of image after sharpening

FUTURE SCOPE

• Increase the accuracy of optical assembly by testing with IR and SMD LEDs.• Expand the utility of the application to other devices.• Use a 35 mm lens (from disposable cameras) to increase the image quality to a great extent.

ENHANCED BINARY IMAGE SENT TO SERVERThe final enhanced image is sent to the Aadhar Authentication Service Agency which sends back the authentication result.

PURPOSE

• This application is developed primarily for capturing the user’s fingerprint using Aakash tablet.

• The existing system uses an external scanner which increases the cost while the system developed by us

uses an optical assembly which uses the Aakash tablet’s camera itself and hence is low cost.• The image captured using the tablet’s camera is later refined and delivered to Authentication Service Agency(ASA) server for the authentication of the Aadhar card holder.

Captured image

ADAPTIVE HISTOGRAM EQUALIZATION (AHE)This step is used to increase the contrast of the image by stretching the histogram.

Image after AHEHistogram of image after AHE

LIVE FINGER DETECTIONIt detects whether the finger is a spoof or not. It converts the RGB image

to grayscale, and then considers the effect of perspiration on it.

IMAGE THRESHOLDINGThe grayscale image is converted to its black and white image by using threshold values. Experimental threshold value : 172

Image after thresholdingHistogram of image after thresholding

IMAGE THINNINGThis step reduces the thickness of the ridges to help easily identify the minutiae.

Image after thinningHistogram of image after thinning

HARDWARE USED:• Black acrylic (3 mm thick)

• Transparent acrylic (3 mm thick, 32.5mm x 35 mm)• PCB • LEDs (4 quantity, 3 mm thick)• Resistors (4 quantity, 220 ohms)• Power source 4.5 V ( 3 AAA (1.5 V) cells in series)

• Switch

Fundamental Research Group, Dept of CSE, IIT BombayCONTRIBUTORS Prashant Main

Sonu Philip

Hitesh Yadav Pooja Deo

Prathamesh PaleyekarSudhanshu Verma

Archana Iyer

Prateek Somani

Summer Internship 2013(9th May to 7th July) email: [email protected]

Optical assembly

Glass plate

Clamp

des