Camouflage BreakingCamouflage BreakingA Review of Contemporary TechniquesA Review of Contemporary Techniques

Amy WhickerAmy WhickerCSCE 867 – Final ProjectCSCE 867 – Final Project

What is camouflage?What is camouflage?

The process of masking the foreground to The process of masking the foreground to appear as though it is background.appear as though it is background.

Camouflage related work can be divided Camouflage related work can be divided into two areas:into two areas:

• Camouflage assessment and designCamouflage assessment and design

• Camouflage breakingCamouflage breaking• Little has been researched in this areaLittle has been researched in this area

Why is camouflage breaking important?Why is camouflage breaking important?

• Military tacticsMilitary tactics

• Background subtractionBackground subtraction

• Helps in the understanding of extraction of Helps in the understanding of extraction of non-camouflaged objectsnon-camouflaged objects

• Helps in developing algorithm to locates object Helps in developing algorithm to locates object in the foregroundin the foreground

Camouflage Breaking MethodsCamouflage Breaking Methods

• Multiple Camouflage Breaking by Multiple Camouflage Breaking by Co-occurrence and CannyCo-occurrence and Canny

Method developed byMethod developed by:: P. Nagabhushan and Nagappa U. P. Nagabhushan and Nagappa U.

BhajantriBhajantri

• Convexity-based Camouflage BreakingConvexity-based Camouflage BreakingMethod developed byMethod developed by::Ariel Tankus and Yehezkel YeshurunAriel Tankus and Yehezkel Yeshurun

Co-occurrence and Canny MethodCo-occurrence and Canny Method

Part 1:Part 1: Determine if there is a camouflaged object Determine if there is a camouflaged object in the image.in the image.

• Create a gray level co-occurrence probability matrix.Create a gray level co-occurrence probability matrix.

• Assess the co-occurrence matrix’s texture parameters.Assess the co-occurrence matrix’s texture parameters.

Part 2:Part 2: Achieve effective visualization of Achieve effective visualization of camouflage objects.camouflage objects.

• Repeatedly apply the Canny edge detection operatorRepeatedly apply the Canny edge detection operator

Calculating the co-occurrence matrixCalculating the co-occurrence matrix

Example from P. Nagabhushan and Nagappa U. BhajantriExample from P. Nagabhushan and Nagappa U. Bhajantri .. Multiple Camouflage Breaking by Co-Multiple Camouflage Breaking by Co-occurrence and Canny.occurrence and Canny.

Results of the Co-occurrence and Results of the Co-occurrence and Canny MethodCanny Method

Images from P. Nagabhushan and Nagappa U. BhajantriImages from P. Nagabhushan and Nagappa U. Bhajantri .. Multiple Camouflage Breaking by Co-occurrence Multiple Camouflage Breaking by Co-occurrence and Canny.and Canny.

Convexity-based MethodConvexity-based Method

• This method uses an operator (DThis method uses an operator (Dargarg) to create an ) to create an

output image whose intensity level is a reflection output image whose intensity level is a reflection of the convexity of the original image.of the convexity of the original image.

• The DThe Dargarg operator is defined by the sum of Y operator is defined by the sum of Yargarg, ,

rotated 0°, 90°, 180°, and 270°.rotated 0°, 90°, 180°, and 270°.

• YYargarg is the y-derivative of the polar coordinates of is the y-derivative of the polar coordinates of

the gradient argument of the original image. Ythe gradient argument of the original image. Yargarg

detects the zero-crossing of the gradient argument.detects the zero-crossing of the gradient argument.

Convexity-based MethodConvexity-based Method

Images from Ariel Tankus and Yehezkel Yeshurun. Images from Ariel Tankus and Yehezkel Yeshurun. A model for visual camouflage breaking.A model for visual camouflage breaking.

Why Convexity?Why Convexity?

Images from Ariel Tankus and Yehezkel Yeshurun. Images from Ariel Tankus and Yehezkel Yeshurun. Convexity-based Camouflage Breaking.Convexity-based Camouflage Breaking.

Thayer’s principle of counter shading

(a)A cylinder of constant albedo under top lighting. (b) A counter shaded cylinder under ambient lighting. (c) Thayer’s principle: the combined effect of counter-shading albedo and top lighting breaks up the shadow effect (or convex intensity function).

Convexity-based MethodConvexity-based Method

• Though edge based methods have their Though edge based methods have their advantages, this method overcomes some of advantages, this method overcomes some of the flaws of an edge-based approach such as,the flaws of an edge-based approach such as,

• Sensitivity to illuminationSensitivity to illumination• ScaleScale• Strong effect of the surroundingsStrong effect of the surroundings• Cluttered or textured imagesCluttered or textured images

How does the Convexity-based method handle How does the Convexity-based method handle changes in Illumination, Scale or Orientation?changes in Illumination, Scale or Orientation?

Images from Ariel Tankus and Yehezkel Yeshurun. Images from Ariel Tankus and Yehezkel Yeshurun. Convexity-based visual Camouflage Breaking.Convexity-based visual Camouflage Breaking.

Convexity-based MethodConvexity-based Method

Images from Ariel Tankus and Yehezkel Yeshurun. Images from Ariel Tankus and Yehezkel Yeshurun. Detection of regions of interest and Detection of regions of interest and camouflage breaking by direct convexity estimation.camouflage breaking by direct convexity estimation.

Invariance to derivable strongly monotonically increasing transformation of the gray-level function.

Convexity-based MethodConvexity-based Method

Images from Ariel Tankus and Yehezkel Yeshurun. Images from Ariel Tankus and Yehezkel Yeshurun. A Model for Visual Camouflage Breaking.A Model for Visual Camouflage Breaking.

Convexity-based MethodConvexity-based Method

Images from Ariel Tankus and Yehezkel Yeshurun. Images from Ariel Tankus and Yehezkel Yeshurun. A Model for Visual Camouflage Breaking.A Model for Visual Camouflage Breaking.

Convexity-based MethodConvexity-based Method

Images from Ariel Tankus and Yehezkel Yeshurun. Images from Ariel Tankus and Yehezkel Yeshurun. Detection of regions of interest and Detection of regions of interest and camouflage breaking by direct convexity estimation.camouflage breaking by direct convexity estimation.

Convexity-based MethodConvexity-based Method

Images from Ariel Tankus and Yehezkel Yeshurun. Images from Ariel Tankus and Yehezkel Yeshurun. Detection of regions of interest and Detection of regions of interest and camouflage breaking by direct convexity estimation.camouflage breaking by direct convexity estimation.

Convexity-based MethodConvexity-based Method

Images from Ariel Tankus and Yehezkel Yeshurun. Images from Ariel Tankus and Yehezkel Yeshurun. Detection of regions of interest and Detection of regions of interest and camouflage breaking by direct convexity estimation.camouflage breaking by direct convexity estimation.

• Co-occurrence and Canny MethodCo-occurrence and Canny Method• AdvantagesAdvantages

• SimpleSimple• Creates a good outline of the objectCreates a good outline of the object

• DisadvantageDisadvantage• Does not extract the objectDoes not extract the object• Must have the known backgroundMust have the known background• Only tested on synthetic images and may not be Only tested on synthetic images and may not be

effective in real applicationeffective in real application

ConclusionConclusion

ConclusionConclusion

• Convexity-based MethodConvexity-based Method• Advantages:Advantages:

• Robust algorithmRobust algorithm

• Precise in finding foreground objectsPrecise in finding foreground objects

• Disadvantage:Disadvantage:• Does not extract the objectDoes not extract the object

• Threshold must be determined, which can change Threshold must be determined, which can change the resultsthe results

ReferencesReferences

[1][1] P. Nagabhushan and Nagappa U. BhajantriP. Nagabhushan and Nagappa U. Bhajantri .. Multiple Camouflage Breaking by Co-Multiple Camouflage Breaking by Co-occurrence and Canny, occurrence and Canny, University of Mysore, Manasa Ganotri, 2004. University of Mysore, Manasa Ganotri, 2004.

[2][2] Ariel Tankus, Yehezel Yeshurun, and N. Intrator. Ariel Tankus, Yehezel Yeshurun, and N. Intrator. Face Detection by Direct Face Detection by Direct Convexity Estimation,Convexity Estimation, Pattern Recognition Letters 18(9) (1997), 913-922. Pattern Recognition Letters 18(9) (1997), 913-922.

[3][3] Ariel Tankus and Yehezkel Yeshurun. Ariel Tankus and Yehezkel Yeshurun. Detection of regions of interest and Detection of regions of interest and camouflage breaking by direct convexity estimation, camouflage breaking by direct convexity estimation, IEEE International Workshop IEEE International Workshop on Visual Surveillance, pages 42-48, Bombay, India, January 1998. In conjunction on Visual Surveillance, pages 42-48, Bombay, India, January 1998. In conjunction with with ICCVICCV 1998. 1998.

[4][4] Ariel Tankus and Yehezkel Yeshurun. Ariel Tankus and Yehezkel Yeshurun. A model for visual camouflage breaking,A model for visual camouflage breaking, 1st 1st IEEE International Workshop on Biologically Motivated Computer Vision (IEEE International Workshop on Biologically Motivated Computer Vision (BMCVBMCV), ), pages 139-149, Seoul, Korea, May 2000. pages 139-149, Seoul, Korea, May 2000.

[5][5] Ariel Tankus and Yehezkel Yeshurun. Ariel Tankus and Yehezkel Yeshurun. Convexity-based camouflage breakingConvexity-based camouflage breaking , , International Conference on Pattern Recognition (International Conference on Pattern Recognition (ICPRICPR), pages 454-457, Barcelona, ), pages 454-457, Barcelona, Spain, September 2000. Spain, September 2000.

[6][6] Ariel Tankus and Yehezkel Yeshurun. Ariel Tankus and Yehezkel Yeshurun. Convexity Based Visual Camouflage Convexity Based Visual Camouflage Breaking,Breaking, Computer Vision and Image understanding 82, (2001) 208-237. Computer Vision and Image understanding 82, (2001) 208-237.