Table 5 BER of watermark images extracted from different attacks.

From: An adaptive robust watermarking scheme based on chaotic mapping

Type of attack

Airplane

Baboon

Goldhill

House

Lake

Peppers

No attack

0

0

0

0

0

0

Salt and pepper noise (m = 0, v = 0.01)

0.0806

0.0946

0.0678

0.0766

0.0687

0.0779

Salt and pepper noise (m = 0, v = 0.05)

0.2601

0.2476

0.2265

0.2382

0.2118

0.2366

Gaussian noise (m = 0, v = 0.01)

0.1643

0.1824

0.1522

0.1463

0.1577

0.1673

Gaussian noise (m = 0, v = 0.05)

0.4082

0.4013

0.3618

0.3632

0.3406

0.3699

Speckle noise (m = 0, v = 0.01)

0.1359

0.1324

0.0679

0.1047

0.0907

0.1119

Speckle noise (m = 0, v = 0.05)

0.3651

0.3064

0.2292

0.2833

0.2461

0.3018

Sharpening

0.1497

0.2515

0.1997

0.1799

0.1718

0.1593

Gaussian filter (3\(\times \)3)

0.0711

0.2201

0.1069

0.1065

0.0766

0.0606

Gaussian filter (5\(\times \)5)

0.1073

0.2780

0.1473

0.1552

0.1125

0.0848

Mean filter (3\(\times \)3)

0.0870

0.2577

0.1307

0.1354

0.0970

0.0742

Mean filter (5\(\times \)5)

0.9818

0.3750

0.2406

0.2588

0.1917

0.1504

Rotation (5\(^\circ \))

0.2105

0.2136

0.2783

0.2360

0.1474

0.1923

Rotation (10\(^\circ \))

0.3026

0.2893

0.2782

0.2783

0.2396

0.2788

Flip vertical

0

0

0

0

0

0

Cropping (10%)

0.0789

0.1726

0.0431

0.1047

0.1561

0.0996

Cropping (20%)

0.2687

0.2564

0.1531

0.2415

0.2867

0.2557

JPEG (QF=90)

0.0080

0.0696

0.0354

0.0175

0.0318

0.0054

JPEG2000 (QF=90)

0.0397

0.1217

0.1327

0.0747

0.0516

0.0426

Gamma correction (gama=0.8)

0.3228

0.3487

0.1588

0.2127

0.1979

0.2508