2013/10/9

Texture Ananlysis

Naoshi Kondo

Division of Environmental Science & Technology,

Graduate School of Agriculture, Kyoto University

KYOTO UNIVERSITY 京都大学 2013/10/9

An energy flow from light source to

output of TV camera

Image grabber and/or PC

Illumination

TV camera

Object

KYOTO UNIVERSITY 京都大学 2013/10/9

Cooccurrence matrix and textural features

Haralick, R.M., K. Shanmugam and Its'hak Dinstein. Textural features for image classification,

IEEE Transactions on systems, man, and cybernetics, Vol.SMC-3, No.6, 610-621.1973.

1

2 3

0 0

0 0

0 2

2

2 2

1

1 1

3

Gray level image

0 1 2 3

0

1

2

3

4 2 1 0

2 4 0 0

1 0 6 1

0 0 1 2

d=1, q =0

Distance and direction

d

q i j

j j

ASM: ΣΣ{p(i,j)} 2 i=0 j=0

n n

ΣΣ p(i,j)/{1+(i-j)2} IDM: i=0 j=0

n n

ΣΣ (i-j)2p(i,j) CON: i=0 j=0

n n

KYOTO UNIVERSITY 京都大学

Measurement Box

Power source, PC,

Spectroscopy,

PLC, amp board

Antenna of DGPS

Chisel

(sensor

probe

housing)

※ Date: 2004. 11. 21 Depth: 150mm, Speed: About 30cm/ sec Cooperation with SHIBUYA MACHINERY CO.,LTD., TUAT

SAS1000 – Outline (Real time soil sensor)

Ready to sell!

Measurement

Nitrogen

MC

SOM

EC

pH

Compaction

+

Image data

2013/10/9

KYOTO UNIVERSITY 京都大学 2013/10/9

Illumination fiber

EC Electrode

Laser Displacement

sensor Color camera Condensed

fiber Ground surface

Soil flattener

Arrangement of equipments in chisel

KYOTO UNIVERSITY 京都大学 2013/10/9

Under-ground-Images by the soil sensor

KYOTO UNIVERSITY 京都大学

Samples of soil images under ground

KYOTO UNIVERSITY 京都大学

a b c

d e f

g h i

(max{a,b,c,d,e,f,g,h,i}-min{a,b,c,d,e,f,g,h,i})×k

(a+b+c+d+e+f+g+h+I)/9

Textural analysis

2013/10/9

KYOTO UNIVERSITY 京都大学 2013/10/9

Machine vision for

fruit grading system

KYOTO UNIVERSITY 京都大学 2013/10/9

Extracted features from images

Sizes Colors Shape Defects Maturity Dullness (Gloss) ……

KYOTO UNIVERSITY 京都大学 2013/10/9

Texture on bioproducts

KYOTO UNIVERSITY 京都大学

Orange fruit sweetness prediction

by human eyes

Color

Size

Shape

Texture

2013/10/9

KYOTO UNIVERSITY 京都大学

Assignment

Describe an image in which textural feature

extraction can be effective process for

discrimination, recognition or

understanding of objects in a page of PPT.

(except images you learnt in this class)

2013/10/9