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S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College...

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SCALED PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.
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Page 1: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

SCALED PATTERN MATCHING

A.Amir Bar-Ilan Univ. & Georgia TechA.Butman Holon CollegeM.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Page 2: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

SEARCHING FOR TEMPLATES IN AERIAL PHOTOGRAPHS

TEMPLATE

INPUT

TASK: Search for all locations where the templateappears in the image.

AERIAL PHOTO

Page 3: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Theoretically, need to consider: Noise Occlusion Scaling (size) Rotation (orientation)

We are interested inasymptotically efficient algorithms

in pixel space.

local errors

Page 4: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

MODEL Low Level (pixel level) avoid costly

preprocessing

Asymptotically efficient solutions.

Serial, exact algorithms.

Page 5: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

TYPES OF APPROXIMATIONS

Local Errors: Level of detailOcclusionNoise

Results:

)log( 2 mnO mismatches

)( 22knO edit distance, k errors,rectangular patterns

)loglog( 2 kkmmknO edit distance, k errors,half-rectangular patterns

AL-88

AF-95

Page 6: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

TYPES OF APPROXIMATIONS

Orientation

Results:

)( 52mnO

)( 32mnO

FU-98

ACL-98

Page 7: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

EVEN WITHOUT ERRORS AND ROTATIONS…

DIGITIZING NEWSPAPER STORIESIDEA: Keep dictionary of fonts

Search for appearances in all size.

Page 8: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

PROBLEM

INHERENTLY INEXACTWhat if appearance is 1½ times

bigger ?What is ½ a pixel ?SOLUTIONS UNTIL NOW:

NATURAL SCALES

Consider only discrete scales

Page 9: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

How does one model for real scales?

Page 10: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

T[7,7]

T[5,4]

T[3,3]T[3,2]T[3,1]

T[2,3]T[2,2]T[2,1]

T[1,3]T[1,2]T[1,1]1

2

3

4

5

6

7

1 2 3 4 5 6 7

Step 1: Define grid & pixel centers.

Example: Unit pixel array for a 77array.

Page 11: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Scaled

To 1⅓

Step 2: Define scaling. Example: 33 array.

Page 12: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.
Page 13: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.
Page 14: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.
Page 15: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.
Page 16: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

ScaledTo 1⅓

Page 17: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Remark: We only scale “up”

Reasons: Avoid conceptual problems of loss

of resolution. From “far enough” away

everything looks the same.

Page 18: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Let P be a mm pattern and T an nn text.

How many different scaled patterns of P are there?

Page 19: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

In fact, can there be two different scaled patterns of P of size kk?

Page 20: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

5×5

Example :

Page 21: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Scaled

by 1.1 to 6x6

4 x 1.1 = 4.4

Page 22: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

4 x 1.125 = 4.5

Scaled

by 1.125 to 6x6

Page 23: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

3 x 1.17 = 3.51

Scaled

by 1.17 to 6x6

Page 24: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

2 x 1.25 = 2.5

Scaled

by 1.25 to 6x6

Page 25: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Let P be a mm pattern and T an nn text.

How many different scaled patterns of P are there?

Page 26: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Claim

There are ≤ nm different scaled patterns representing all the occurrences of P.

Page 27: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

mm, (m+1)(m+1), … , nn

n-m different possible sizes

Each one has at most m possible matrices representing it

Proof:

Page 28: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Each one has at most m possible matrices representing it

Proof:

Why?

Page 29: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Distance = 1

Page 30: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

… …

Pattern P scaled to size k×k,

… …

)k)×(½-k(½-

…… …

)k)×(½+k(½+

Page 31: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

1

Page 32: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Therefore

There are ≤ nm different scaled patterns representing all the occurrences of P.

Page 33: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Algorithm outline for 2-D scaled matching

Page 34: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Straightforward Idea Construct dictionary of O(nm)

possible scaled occurrences of P.

Use 2-dimensional dictionary matching algorithm to scan the text in linear time and find all occurrences.

Page 35: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Space and Time Analysis

mm, (m+1)(m+1), … , nn

Dictionary size O(n3m)

Each one has at most m possible matrices representing it

Page 36: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Solution

Our idea is to keep the dictionary in compressed form.

The compression we use is run-length of the rows.

Page 37: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Run-length

aabcccbba2b1c3b2

Page 38: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

ABC

DEF

GHI

AABBBCC

AABBBCC

DDEEEFF

DDEEEFF

DDEEEFF

GGHHHII

GGHHHII

ScaledTo 2⅓

The compressed dictionary

Page 39: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

AABBBCC

AABBBCC

DDEEEFF

DDEEEFF

DDEEEFF

GGHHHII

GGHHHII

Compressedform

A2B3C22

D2E3F23

G2H3I22

#of repetitions of row

Page 40: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

A2B3C22

D2E3F23

G2H3I22

#of repetitions of row

Size of Array: mxm# of diff. scaled patterns: (n-m) x m

Dictionary size: O(nm3)

Page 41: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

The Idea behind the text searching

For every text location [i,j], we assume that there is a pattern scaled occurrence beginning at that location.

Subsequently, we establish the number of times this row repeats in the text.

This allows us to an appropriately scaled pattern row from the dictionary.

Page 42: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Example for text searching

c100ba

c100ba

.

.

.

c100ba

.

.

.

.

.

.

102

2

1

.

.

.

P:

d150cb10

c150ba10

c150ba10

…c150ba10

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

1

2

133

132

.

.

.

.

.

.

T:

Page 43: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

…c150ba101

aaaaaaaaaa

Page 44: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

Look in the text location [1,10]

c100ba

c100ba

.

.

.

c100ba

.

.

.

.

.

.

102

2

1

.

.

.

P:

d150cb10

c150ba10

c150ba10

…c150ba10

.

.

.

.

.

.

.

.

.

.

.

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.

1

2

133

132

.

.

.

.

.

.

T:

Page 45: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

c100ba

c100ba

.

.

.

c100ba

.

.

.

.

.

.

102

2

1

.

.

.

P:

d150cb10

c150ba10

c150ba10

…c150ba10

.

.

.

.

.

.

.

.

.

.

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.

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.

.

.

.

.

.

.

1

2

133

132

.

.

.

.

.

.

T:

Page 46: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

…c150ba101

Page 47: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

…c150ba101

aaaaaaaaaab

Page 48: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

…c150ba101

aaaaaaaaaabccccccccccccccc…

Look in the text location [1,10]

Page 49: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

c100ba

c100ba

.

.

.

c100ba

.

.

.

.

.

.

102

2

1

.

.

.

P:

d150cb10

c150ba10

c150ba10

…c150ba10

.

.

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.

1

2

133

132

.

.

.

.

.

.

T:

22

2½2½

Page 50: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

c100ba

c100ba

.

.

.

c100ba

.

.

.

.

.

.

102

2

1

.

.

.

P:

d150cb10

c150ba10

c150ba10

…c150ba10

.

.

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.

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1

2

133

132

.

.

.

.

.

.

T:

A scale

range of

[ 1,1¼(

Page 51: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

c100ba

c100ba

.

.

.

c100ba

.

.

.

.

.

.

102

2

1

.

.

.

P:

d150cb10

c150ba10

c150ba10

…c150ba10

.

.

.

.

.

.

.

.

.

.

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.

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.

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1

2

133

132

.

.

.

.

.

.

T:Last symbol may repeat in the text more time than the scaled pattern need.

Page 52: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

What about the number of times the first subrow repeats?

c100ba

c100ba

.

.

.

c100ba

.

.

.

.

.

.

102

2

1

.

.

.

P:

d150cb10

c150ba10

c150ba10

…c150ba10

.

.

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1

2

133

132

.

.

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.

.

.

T:

Page 53: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

The range of [1,1¼) is valid since 102ⅹ1¼=128<132.

c100ba

c100ba

.

.

.

c100ba

.

.

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.

102

2

1

.

.

.

P:

d150cb10

c150ba10

c150ba10

…c150ba10

.

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1

2

133

132

.

.

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.

.

.

T:

Page 54: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

c100ba

c100ba

.

.

.

c100ba

.

.

.

.

.

.

102

2

1

.

.

.

P:

d150cb10

c150ba10

c150ba10

…c150ba10

.

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.

.

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1

2

133

132

.

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.

.

T:

Look in the text location [1,9]

Page 55: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

c100ba

c100ba

.

.

.

c100ba

.

.

.

.

.

.

102

2

1

.

.

.

P:

d150cb10

c150ba10

c150ba10

…c150ba10

.

.

.

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1

2

133

132

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.

.

T:

2½2½

3½3½

Page 56: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

c100ba

c100ba

.

.

.

c100ba

.

.

.

.

.

.

102

2

1

.

.

.

P:

d150cb10

c150ba10

c150ba10

…c150ba10

.

.

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.

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1

2

133

132

.

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.

T:

A scale

range of

[ 1,¼1¾(

Page 57: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

c100ba

c100ba

.

.

.

c100ba

.

.

.

.

.

.

102

2

1

.

.

.

P:

d150cb10

c150ba10

c150ba10

…c150ba10

.

.

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.

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1

2

133

132

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.

T:

Too large,it requires the c

to repeat 175 times.c

c150

Page 58: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

c100ba

c100ba

.

.

.

c100ba

.

.

.

.

.

.

102

2

1

.

.

.

P:

d150cb10

c150ba10

c150ba10

…c150ba10

.

.

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1

2

133

132

.

.

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.

.

.

T:The range is reduced to

[1,¼1 ( 204101

Page 59: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

c100ba

c100ba

.

.

.

c100ba

.

.

.

.

.

.

102

2

1

.

.

.

P:

d150cb10

c150ba10

c150ba10

…c150ba10

.

.

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.

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.

.

.

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1

2

133

132

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.

T:

152

[1,¼1( This is still to large for the vertical scale.

204101

Page 60: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

c100ba

c100ba

.

.

.

c100ba

.

.

.

.

.

.

102

2

1

.

.

.

P:

d150cb10

c150ba10

c150ba10

…c150ba10

.

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1

2

133

132

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T:

The maximum scale valid for both horizontal and vertical scales produces the pattern whose first row is a2bc129 and which repeats 132 times.

Page 61: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

c100ba

c100ba

.

.

.

c100ba

.

.

.

.

.

.

102

2

1

.

.

.

P:

d150cb10

c150ba10

c150ba10

…c150ba10

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

1

2

133

132

.

.

.

.

.

.

T:The range is reduced to

[1,¼1 ( 20457

Page 62: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

OPEN PROBLEM:

Give algorithm linear in run-length compressed text and pattern.

Page 63: S C A L E D PATTERN MATCHING A.Amir Bar-Ilan Univ. & Georgia Tech A.Butman Holon College M.Lewenstein Bar-Ilan Univ. E.Porat Bar-Ilan Univ.

END


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