research and machine vision - modified

8/3/2019 Research and Machine Vision - Modified

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Research and Machine Vision

Joel P. Ilao

November 23 & 26, 2011


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Some Philippine Facts 2,180 HEIs: 607 public, 1573 private ( from CHED

website) no PH university in top 300 of World University

Rankings, 2011 (DLSU: 451-500). 3 PH universities.

PH ranked 75th out of 142 countries in GlobalCompetitiveness Report 2011-2012 (up by 10spots from last year) by World Economic Forum

(WEF) improved by 2 points in Higher Educ. Category and

training


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Taken from Unesco Institute for Statistics (UIS) Fact Sheet (August, 2011)


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country Year Population

(in Millions)

RSE per million

PH 2005 92.2 81

SG 2007 5 6088

TH 2005 63.4 311

ID 2005 231.4 162

VN 2002 85.8 115

Source:

Unesco Science Report, 2010


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DOST National Science and Technology

Plan (NSTP) for 2002-2020 Long Term Area thrusts

agriculture, forestry and natural resources

health / medical sciences

biotech

ICT

m croe ec ron cs

material sciences and engineering

earth and marine sciences

fisheries and aquaculture

environment

natural disaster mitigation

Energy

manufacturing and process engineering


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Research Process


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Research Process


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Digital Image Processing DIP is the analysis and manipulation of

digitized images through the use of computer

-Image

Compression3-D Vision

Image

Segmentation

FilteringPattern

Recognition

Noise Reduction

in Images


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System FlowchartsInput

Pre-processing

Feature

Extractor

Main Algo

Post-processing

Output

Algo 1 Algo 2

Combine

Intermediate

Output

Database


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Tools for conducting research Hardware:

computer

camera

so ware: Matlab and Matlab clones

Octave, Mathematica, SciLab

IDEs with image processing libraries openCV for C/C++, AForge.Net for C#, etc.


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REVIEW OF DSP


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Signal Modification Amplification

Sub-sampling / scaling

)()( txty =

)()( ktxty =


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Linear Systems Definition: A system is linear iff it satisfies:

Example in DIP:

[ ])()()()( 22112211 txtxHtyty +=+

AWGN ri ing on igita images Transfer function: y = f(x,y)

one interesting problem in DIP is estimation of

transfer function

application in super-resolution


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Time vs. Frequency Domain Converting from time to freq. domain and

back Fourier Transform

other transforms: (i.e. wavelet transform, discrete

cosine transform, etc.)


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Histogram Analysis Image Segmentation


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SAMPLE MV AND DIP PROJECTS


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Vision-based Vehicle Tracking


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Overall Block DiagramHypothesis Generation

Block


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Finding vehicles based on contour

(Hypothesis Verification)


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Finding vehicles based on contour

(Hypothesis Verification)


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License Plate Recognition


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Vision-based Object Counting System


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Vision-based Object Counting System

Image

Preprocessing

Object

Segmentation

Attribute

Extraction

Noise

suppressedimage

Segmentedobjects

Attribute

values

Reference

image

ComparisonUser

Display

Results

Results

Reference

Attribute

Database

attribute

values

Selected

attributes

Input image

file


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Human Gait Analysis

0 50 100 150 200 250 300 350 4000

10

20

30

40

50

60

70


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Humain Gait Analysis


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Depth Estimation and Image

Segmentation using Monocular Images


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Facial Expression Tracking and Mimicking


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Facial Expression Tracking and Mimicking


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Fingerprint Authentication


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Fingerprint Identification


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Fingerprint Identification


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Vision-based Hand Mimicking System

Left Image

Right Image


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Vision-based Hand Mimicking System

User

Image AcquisitionModule

Hand Movements

Segmented

2D Points Tracker

Module

Angle Reconstruction

Module

Simulation Module

Colored Image

Angles of

Hand Parts

2D Coordinates of

Hand Parts

3D Reconstructed

Model

Angles of

Hand Parts

Instruction


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Assignment for next meeting Group yourselves into groups of 4

Each group will propose system architectures/block diagrams and flowcharts for (a) a

,

their choice.

keep proposals unique and creative

include references when needed clearly state reasons for choices


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Sample MV problem

(chick counter)

research and machine vision - modified

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