The World vs. SCOTT

Synthesis of COncealment Two-level Texture

Julien Gosseaume, Kidiyo Kpalma and Joseph Ronsin

Universite Europeenne de Bretagne, 35000, Rennes, France

INSA, IETR, UMR 6164, F-35708, Rennes, France

Keywords:

COncealment, Two-level Texture, Concealment Texture, Texture Synthesis, Image Analysis, Human Visual

System HVS.

Abstract:

We propose an original method of Synthesis of COncealment Two-level Texture (SCOTT). SCOTT was de-

signed according to the Human Visual System so that the concealment texture is faithful to the visual environ-

ment it will be placed in, in terms of forms and colors. The results of simulation prove that the concealment

texture is efﬁcient although it is made of simple forms and only a few colors. Even if SCOTT has initially

been designed for an application of reducing the visual pollution caused by manmade equipments (antenna,

electrical cabinets, distributor boxes, repeater shelters, etc.), it may be used in many applications, such as

inpainting, and even in image compression.

1 INTRODUCTION

We propose an original method of Synthesis of COn-

cealment Two-level Texture (SCOTT), which pro-

vides a texture faithful to the visual environment it

will be placed in, while having simple forms and only

a few colors. The purpose of a concealment texture

is to be both generic enough to be placed at differ-

ent positions and viewpoints in a scene, and accurate

enough to be efﬁcient, at different scales. It is a trade-

off between genericity and efﬁciency. Based on the

Human Visual System, SCOTT synthesizes a “two-

level texture” which is a mix between a macro-texture

and a micro-texture. The macro-texture represents the

global aspect of the concealment texture, i.e. its dom-

inant forms. In case of a regular texture, the global

aspect is given by the primitives, like the bricks of

a brick wall. Similarly, the micro-texture represents

the local aspect of the concealment texture, i.e. the

details inside the dominant forms. In case of a reg-

ular texture, the local aspect is given by the random-

like distribution of colors inside the primitives, like

the appearance of “grain” at the surface of a brick.

So the concept of “macro” and “micro” depends of

the scale of observation. A macro-texture becomes a

micro-texture when observed at a longer distance; on

the contrary, a micro-texture becomes a macro-texture

when observed at a shorter distance. This duality can

be found in various natural (e.g. a pebble beach) and

artiﬁcial (e.g. a brick wall) structures. In the case

of a computer-generated texture, such a duality gives

the texture a visual richness which makes it more re-

alistic; we can compare the video games issued ten

years ago, and those recently issued: the richness of

the textures make them more “true”. It is important to

keep in mind that our goal is not to synthesize a tex-

ture exactly the same as a given visual environment;

our need requires a trade-off between genericity and

efﬁciency.

2 PROPOSED METHOD

SCOTT has been designed according to the the Hu-

man Visual System, and synthesizes a two-level tex-

ture, based on a mix of a macro-texture and a micro-

texture. The fusion of these two levels of texture gives

a realistic ﬁnal texture, faithful to the visual environ-

ment it will be placed in.

2.1 Human Visual System

An object is concealed if it has the same dominant

colors and the same dominant forms as its visual en-

vironment (Julesz, 1999). These two global conceal-

ment rules, having the same dominant colors and the

same spatial frequency spectrum (dominant forms),

257

Gosseaume J., Kpalma K. and Ronsin J..

The World vs. SCOTT - Synthesis of COncealment Two-level Texture.

DOI: 10.5220/0004659502570264

In Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISAPP-2014), pages 257-264

ISBN: 978-989-758-003-1

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

are deﬁned according how of the Human Visual Sys-

tem receives and processes the visual information.

The visual information is borne by the “color”, as a

sum of visible frequencies. These electro-magnetic

frequencies are received by the retina, and the color

perceived by the brain depends on the frequency re-

sponse of the rods and cones inside the retina. A user-

friendly way to represent the perceivable colors is the

HSV (Hue, Saturation, Value) colorspace. When one

sees an object, the color information is processed in

the primary visual cortex V1 to extract the color con-

trasts. These contrasts allow higher cortical areas to

extract forms, which may ﬁnally be identiﬁed by even

higher cortical areas (Buduc, 2012).

Then the HSV works like an interpreter, going

from concrete low-level pieces of information, that is

the electro-magnetic spectrum of the light received,

to abstract high-level semantic concepts (e.g.: “a blue

small car”).

So an object may be identiﬁed if there exists a con-

trast between this object and its visual environment,

in terms of colors or the distribution of the colors

(forms) (Landragin, 2004; Baumbach, 2010). In other

words, an object will not be identiﬁed, nor detected,

if it has the same colors, and the same forms (spatial

frequency spectrum), as its visual environment.

Even if such a representation of the HSV remains

very simplistic, its level of precision is enough for our

need: it is not to create an exhaustive model of the

HSV to make objects invisible (for the concealment

of distributor boxes, it would indeed be difﬁcult to

maintain them if they cannot be located!), but to re-

duce the visual pollution by giving the “polluants” an

aesthetically more pleasing look. For further infor-

mation, the reader is invited to have a “look” at refer-

ences (Julesz, 1999; Buduc, 2012; Landragin, 2004;

Baumbach, 2010).

2.2 Synthesis of COncealment Two-level

Texture

From our study of the Human Visual System, we

deﬁned two general concealment rules: “having the

same dominant colors” and “having the same domi-

nant forms”. SCOTT is then built around these two

components: computing the colors and the forms

(Julesz, 1999).

To make the concealment texture faithful to the

visual environment it will be placed in, it is synthe-

sized according to a two-level concept, like in the

case of a brick wall: the global aspect of the walls,

as a concatenation of bricks, is its macro-texture. So

the macro-texture (coarse texture) corresponds to the

dominant forms and colors of the concealment tex-

ture. And the local aspect of the wall, that is the de-

tails inside one particular brick, is its micro-texture.

So the micro-texture (ﬁne texture) corresponds to the

secondary colors and forms of the concealment tex-

ture. In other words, the duality macro-texture/micro-

texture can be viewed as the duality global/local ap-

pearance of the texture, depending on the scale con-

sidered.

We have to keep in mind that the purpose of a con-

cealment texture is to be both generic enough to be

placed at different positions in a scene, and accurate

enough to be efﬁcient, at different scales. It is a trade-

off between genericity and efﬁciency.

So SCOTT computes the concealment texture

from two input models: one model for the macro-

texture (coarse texture) and one model for the micro-

texture (ﬁne texture); SCOTT ﬁrst computes the

macro-texture and the micro-texture independently,

and then mixes them to synthesize the concealment

texture (Figure 1). For the moment the two input

models are selected manually, then the choice is sub-

jective.

2.2.1 Synthesis of Macro-texture

The macro-texture, i.e. the dominant colors and forms

of the concealment texture, represents the coarse tex-

ture of the concealment texture. The macro-texture

makes the concealment efﬁcient at long distances of

observation. These colors and forms are computed

from the macro-texture model. This model must be

representative of the global aspect that the user wants

the texture of dissimulation to look like. The com-

putation of the macro-texture is divided into 3 steps

(Figure 1):

1. Extracting Dominant Colors. From the L*a*b*

histogram of the macro-texture model, the domi-

nant colors are extracted. The L*a*b* colorspace

has been chosen because it has been designed so

that a Euclidian distance computated inside this

colorspace corresponds to a visual distance. The

number of dominant colors to extract depends

on the colorimetric content of the macro-texture

model.

2. Extracting Dominant Forms. The forms (re-

gions) are extracted using a segmentation of the

pixels of the same model. To do so, we use

a k-means clustering (MacQueen, 1967) process

based on the L*a*b* components of the pixels

of the macro-texture model. The “clustering” ef-

fect in the L*a*b* colorspace is then equivalent

to a segmentation in the image space, since the

forms are perceived by the Human Visual System

as contrasts of colors.

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258

3. Combining Colors and Forms The dominant

colors are combined with the dominant forms, by

computing the Euclidian distances between the

dominant colors and the mean colors inside the

dominant forms, in the L*a*b* colorspace. The

combination is done in a way that each dominant

form has a different dominant color and the MSE

of the combination is minimized.

At this step we have a simple macro-texture with

coarse forms and only a few colors, which makes the

concealment efﬁcientat long distances of observation.

2.2.2 Synthesis of Micro-texture

The micro-texture, i.e. the secondary colors and

forms of the concealment texture, represents the ﬁne

texture of the concealment texture. Contrary to the

the macro-texture which makes the concealment ef-

ﬁcient at long distances of observation, the micro-

texture makes the concealment efﬁcient at short dis-

tances of observation. At medium distances, both

macro-texture and micro-texture are efﬁcient in their

own role. This ﬁne texture makes the concealment

texture more faithful to the visual environment. The

idea behind adding a ﬁne texture to the coarse texture

is to make the spatial frequency spectrum of the con-

cealment texture more “rich” by adding high frequen-

cies through random-like small forms; indeed the nat-

ural scenes generally have random-like small forms.

The forms of the ﬁne texutre are computed from the

micro-texture model. The micro-texture model may

be totally independent from the macro-texture model.

The only requirement for this model is that it must be

stochastic: sand, grass, etc. So the name of the game

is to make the ﬁne texture appear at short distances of

observation, while preserving the forms of the macro-

texture at long distances of observation, like in the

case of a brick wall. The computation of the micro-

texture is divided into 2 steps (Figure 1):

1. Resizing the Model. The micro-texture model

is resized to ﬁt the size of the macro-texture. If

the micro-texture model is bigger than the macro-

texture, it is simply cropped. If it is smaller, a new

model is synthesized with a patch-based synthesis

(Finkelstein and Hoppe, 2000) using the micro-

texture model: the model is divided into blocks

called “patches”, and a new texture (whose size is

that of the macro-texture) is synthesized by ran-

domly concatenating thoses patches.

2. Extracting the Dominant Forms. The dominant

forms are extracted from the resized micro-texture

model with the same process as for the macro-

texture: k-means clustering. Theses forms must

be superimposed on those of the macro-texture to

mix both the macro-texture forms and the micro-

texture forms.

2.2.3 Mixture of the Micro-texture with the

Macro-texture

According to the behavior of the Human Visual Sys-

tem, a form is noticeable if its inner color contrasts

with the colors around. So to mix the micro-texture

with the macro-texture, we use this principle the

other way around. Since we want the micro-texture

to be visible above the macro-texture, we make the

macro-texture colors, precisely the L* component

in L*a*b* colorspace, vary according to the micro-

texture forms. The micro-texture is used as a mask

above the macro-texture and increases/decreases the

L* component of the pixels in the macro-texture un-

derneath.

The third step of SCOTT allows the micro-texture

to be superimposed on the macro-texture, giving the

ﬁnal concealment texture a visual “richness” which

makes it more realistic.

Finally, after the entire SCOTT process (Figure 2),

we obtain a concealment two-level texture which is

faithful to the visual environment it will be placed in,

while having simple forms and only a few colors.

Macro-texture

model

Micro-texture

model

Extracting

dominant

colors

Extracting

dominant

forms

Combining

colors / forms

Resizing

Extracting

dominant

forms

Mixing

micro-texture with

macro-texture

Concealment

two-level

texture

Macro-texture Micro-texture

Figure 1: SCOTT is based on a “two-level” texture concept,

mixing a micro-texture (dashed lines) with a macro-texture

(solid lines), from two input models.

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259

(a) Macro-texture model (b) Micro-texture

model

(e) Macro-texture dominant forms

with dominant colors

(f) Resized micro-texture dominant

forms

(g) Final 2-level concealment tex-

ture

Figure 2: The concealment texture is based on a two-level concept. The concealment macro-texture corresponds to the

coarse texture, and is synthesized from the ﬁrst input sample (a). The dominant forms (d) and colors are combined (e). The

concealment micro-texture corresponds to the ﬁne texture, and is synthesized from the second input sample (b). The sample

is resized (c) to ﬁt the size of the concealment macro-texture. Then the dominant forms (f) are extracted to be mixed with

those of the concealment macro-texture. The mixture is made by using the micro-texture dominant forms as a mask above the

concealment macro-texture, and making the colors of the concealment macro-texture vary (brighter or darker), according to

the micro-texture dominant forms above (g).

3 RESULTS OF SUBSTITUTION

SCOTT will then synthesize a texture faithful to the

visual environment it will be placed in, while having

simple forms and only a few colors. So far, the num-

ber of dominant colors needs to be manually adjusted

according to the color “richness” of the visual envi-

ronment.

To evaluate how faithful the concealment texture

is to its visual environment, we placed the conceal-

ment texture in the visual environment, at the ex-

act same position as that of the sample used for the

macro-texture model. It is a purely qualitative and

subjective evaluation, since we have no quantitative

and objective metrics in line with our need (Section

5).

The results in an application of substitution

demonstrates that the proposed method can synthe-

size a texture using only simple forms and a few col-

ors, with the same visual aspect as its environment

(Figure 3). It is indeed difﬁcult to see the difference

between the textures. These results demonstrate the

two rules deﬁned: “having the same dominant col-

ors” and “having the same dominant forms”. We still

have to keep in mind that our goal here is not to syn-

thesize a texture exactly the same as a given visual

environment; the purpose of a concealment texture is

to be both generic enough to be placed at different po-

sitions in a scene, and accurate enough to be efﬁcient,

at different scales. So our goal is a trade-off between

genericity and efﬁciency.

A way to evaluate the concealment texture in

terms of colors and forms is to process the original

image and the image with concealment textures with

a Gaussian ﬁlter and a Sobel ﬁlter (Figure 4) and vi-

sually comparing the results. Indeed, processing an

image with a Gaussin ﬁlter gives an overview of its

dominant colors; and processing an image with a So-

bel ﬁlter gives an overview of its dominant forms, by

extracting the edges. This way we can subjectively

evaluate if the image with a concealment texture has

the same dominant colors and forms as the original

image (Figure 4).

The results for an application of substitution prove

that SCOTT synthesizes a texture not very salient. For

a concrete application of concealment (Section 4), the

results of simulation prove that SCOTT synthesizes

a concealment texture which can be placed at differ-

ent positions in a given visual environment, in order

to conceal different objects. SCOTT is then a good

trade-off between genericity and efﬁciency.

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Figure 3: The concealment two-level texture is faithful to the visual environment, while having simple forms and only a few

colors. In the left column is an original image from which have been extracted two samples for the concealment texture

synthesis, i.e. the macro-texture and micro-texture models. In the middle column is the same image with the ﬁrst input

sample replaced by the corresponding concealment two-level texture. Since the position of those samples is not given in these

images, the results show that it is almost impossible to notice any difference between the original image and the one with the

concealment texture. The position of the concealment texture is only revealed in the right column. An interesting exercise is

to make someone, unaware of such an application of concealment, watch only the images in the left and middle columns to

prove that the concealment texture is unnoticeable.

Figure 4: The concealment two-level texture is faithful to the visual environment because its dominant colors and forms do

not create artiﬁcial saliency. In the left column an original image has been processed with a Gaussian ﬁlter (top row) and

a Sobel ﬁlter (bottom row). In the middle columns the same image with a concealment texture (at the exact same position

as that of the macro-texture model) has been processed with the same ﬁlters. A qualitative comparison between the original

images and the same image with a concealment texture shows that the concealment texture has the same dominant forms and

colors as its environment. That is why it does not create any artiﬁcial saliency.

(a) (b) (c)

Figure 5: The initial application of SCOTT is the concealment of objects. SCOTT takes two models from a visual environment

(a) and synthesizes a concealment two-level texture. A same texture can conceal several different objects (b). The concealed

objects are hardly detectable because they are not salient anymore (c).

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Figure 6: SCOTT makes the visual pollution much less salient. In a concrete case of applying a SCOTT-synthesized conceal-

ment texture (middle column), a realistic simulation makes any big “polluant” (left column) much less salient by giving it an

aesthetically more pleasing look (right column).

4 APPLICATIONS

SCOTT may be used in various applications. The ini-

tial application of SCOTT is the concealment of ob-

jects to reduce visual pollution (Dandumont, 2013):

antenna, electrical cabinets, distributor boxes, re-

peater shelters, etc. Results of simulation show that

SCOTT is really efﬁcient by synthetizing a unique

concealment texture which makes different objects

much less salient (Figure 5). To make the simula-

tion simple and fast, the concealment texture has been

computed and placed in the image, superimposed on

the objects to conceal in the image, and then does not

ﬁt their shapes and orientations.

To have a clear idea of what such a conceal-

ment would be in a concrete case, we conducted a

more sophisticated simulation of a concealment using

SCOTT-synthesized concealment texture. Even if the

“polluant” is quite big, the concealment texture makes

it much less salient by giving it an aesthetically more

pleasing look. Once again, by processing the images

with a Gaussian ﬁlter and a Sobel ﬁlter, we can quali-

tatively evaluate the performance of SCOTT as it de-

creases the saliency of the concealed object (Figure

7).

Another application for SCOTT is inpainting

(Bruno et al., 2000), which consists in repairing a

“hole” in an image. Then the results are the same as in

the case of concealment application. A SCOTT-based

inpainting application could be useful, for example,

in 3D video-mapping technology.

Finally, since SCOTT synthesizes a texture which

has the same visual aspect as its environment, while

having simple forms and only a few colors, SCOTT

could be used in an image compression process, when

only a few details are needed in somes textures: video

games, etc.

5 FUTURE WORK

The results of simulation prove that the concealment

is qualitatively and subjectively efﬁcient. But we

presently have no quantitative and objective metrics

to evaluate its visual impact. Such metrics would au-

tomatically reproduce the subjective assessment of a

viewer in front the visual environment contraining the

SCOTT-synthesized concealment texture. Some met-

rics actually exist to evaluate the visual similarity be-

tween two images, like SSIM (“Structural SIMilar-

ity”) (Wang et al., 2004), which is usually used to

measure the visual quality of an image with distor-

sions, based on an initial distorsion-free image as ref-

erence. Even if SSIM is based on the Human Visual

System (HSV), by considering image degradation as

perceived change in structural information, it is only

applied on the luma, and then does not reproduce the

entire behavior of the HVS. Futhermore, it is not ap-

plicable in our application for two reasons: ﬁrst SSIM

is applied on the entire images, so the smaller the con-

cealment texture, the better the SSIM value; secondly,

it goes against our goal since the concealment is to

modify the input image structure to make an object

less salient, then the SSIM value would always be

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Figure 7: SCOTT uses the dominant colors and forms of the environment. In a realistic simulation, when we process the

original image of a visual environment, and its version with the concealment texture (left column) with a Gaussian ﬁlter

(middle column) and a Sobel ﬁlter (right column), we can qualitatively conclude that the concealed object is less salient

because it has the same dominant colors and forms its environment. Indeed it is more difﬁcult to detect the “polluting” with

the concealment texture (ﬁrst and third rows) than without the concealment texture (second and fourth rows).

small.

The future work will then be the conception of an

objective estimator, based on a HVS model, which

would analyze the scene containing the concealment

texture. A lead is the use of a “saliency map”, which

reveals what is salient to the HVS, i.e. what catches

the attention of an observer in front of a given scene.

Since the purpose of the concealment texutre is to

make an object unnoticeable, a saliency map, cor-

rectly based on the HSV response, would reveal that

the concealment textures in the resulting images (Fig-

ure 6) are not salient, i.e. they would catch no one’s

attention.

6 CONCLUSIONS

Based on the Human Visual System, we propose

an original method of concealment texture synthesis:

SCOTT (“Synthesis of COncealment Two-level Tex-

ture”).

The results prove that the concealment texture is

efﬁcient, evenif it is made of simple forms with only a

few ﬁnal colors; besides, a same concealment texture

can be used to conceal several different objects.

Next step will be to conceive an objective mea-

sure to evaluate our results, by taking into account the

HVS response to them. This will give us a feedback

on our work.

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Besides, an application of image compression

could make use of such a texture synthesis method, by

replacing non-salient samples by substitute textures,

in a given image.

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