Mr.R.SANJEEV KUNTE B.E,M.Tech,Phd

Professor, Dept of CS & E,JNNCE, Shimoga.

Under the Guidance of

FIRST PROJECT SEMINAROn

MOBILE DOCUMENT RETRIVER

Jawaharlal Nehru National College of Engineering, Shimoga – 577204Department of Computer Science & Engineering

GIRISH.A 4JN07CS025JAIMINI.M.TAPAS 4JN07CS028PRADEEP.P 4JN07CS056SUSHRUTH.D.BELAGUR 4JN07CS097

Presented by

Mrs.Poornima K.M B.E,M.Tech

Asst.Professor, Dept of CS & E,JNNCE, Shimoga.Mr. Chetan K.R B.E,M.Tech

Sr.Lecturer, Dept of CS & E,JNNCE, Shimoga.

Project Coordinators

CONTENTS

1.Abstract.2.Introduction to the area.3.Application4.Problem Specification.5.Literature Survey and Summary.6.System Architecture.7.References.

ABSTRACT:-

• The popularity of camera phones enables many exiting multimedia applications. A camera based document image retrieval system which is targeted towards camera phones. Mobile document retriever application allows user to interact with paper documents, books, magazines, etc... Interaction is between physical and digital world is achieved by pointing camera at a patch of text on a document and sending it to the server where it is matched and corresponding information is retrieved.

INTRODUCTIONMobile applications Mobile Apps are apps or services that can be pushed to a

mobile device or downloaded and installed locally. Classification

• Browser-based: apps/services developed in a markup language

• Native: compiled applications (device has a runtime environment). Interactive apps such as downloadable games.

• Hybrid: the best of both worlds (a browser is needed for discovery)

Mobile Platforms• A wide variety of device supporting different platforms

Windows MobileBlackBerryPalm OSSymbian

• RunTime environment and appsBrowser-based apps (WAP)Flash-liteJava MEQualcomm’s BREWGoogle’s Android

OVERALL PROCESS

APPLICATIONS

• Real Estate Guide

• Advertisement posters

• IT administrators to quickly learn server configuration details

• Conference room application

• Retrieving imaged documents in digital libraries and offices.

Real estate guide

• Synchronization of mobile with pc and database

Advertisement poster

• URL’s used on the posters can be used to obtain more

information regarding poster

IT administrator to quickly learn server details• Configuration details are immediately available on mobile

screen and can get required information.

Conference room application

• pending

Problem specification

• pending

Technical Challenges

• Most of camera enabled mobiles lack macro and auto-focus facility to get better quality of image.

• Achieving good Network Latency.• Providing language independency.• Searching time should be minimal even

though the database is larger.• Handling of distorted image to certain

extent.

Significance

• As mobile has become part of our life it is better that we have more and more options in mobile to perform various tasks in it.

• Linking physical and digital world would ease many work

Literature survey

OCR Technology

• It examines scanned bitmap images of machine-printed text and translates the characters into ASCII text files that can be edited.

• It is widely used to convert books and documents into electronic files, to computerize a record-keeping system in an office etc..

• OCR recognition technology requires high-quality images with excellent contrast, character and clarity. 

Feature extraction

• Transforming the input data into the set of features is called feature extraction.

• It involves simplifying the amount of resources required to describe a large set of data accurately.

• It can be used in the area of image processing which involves using algorithms to detect and isolate various desired portions or shapes (features) of a digital image. 

Mobile RetrieverXu Liu ,David Doermann

• OCR is applied to the documents while retrieving from the database.

• It is proposed that token pairs and triplets which respectively retrieve and verify the candidates of retrieval at high speed and accuracy.

Mobile visual search, linking printed documents to digital media

xu liu, Jonathan J,Hull

• Feature extraction method is used in retriving documents from the database.

• Quality of the input image is estimated before sending it to recognition.

• Recognition takes place based on image features extraction and efficient database lookup

Document Image Matching and retrieval with Multiple Distortion-

Invariant DescriptorsJonathan J. Hull

• setup time (compile the database)for each image in the database1. locate features in the image

2. calculate descriptors from groups of features

3. enter passage identifier and location in a hash table

• run time (match a query image to the database)1. locate features in the input image2. construct descriptors from groups of features3. for each descriptor

increment accumulator cell corresponding to eachpassage identifier

Document Finder

• Here kd-tree is used to retrieve documents from database.

• Kd-tree is a popular data structure for fast data point search.

• It is used with SIFT for retrieving.

Mobile Document Retrieval Architecture

Mobile Document Retrieval Architecture