Colour and Texture
Extract 3-D information Using
• Extract 3-D information for performing certain
tasks such as manipulation, navigation, and
• There are three aspects of this:
– Segmentation of the scene into distinct objects
– Determining the position, orientation and shape of
each object relative to the observer
– Feedback to modify the motion of the robot
How Do We Recover 3-D
• There are number of cues available in the
– Binocular stereopsis
• Each of these cues relies on background
assumptions about physical scenes in order to
provide unambiguous interpretation.
Studies by psychologist and artists have demonstrated that the
presence and distribution of colours induce sensations and
convey meanings in the observer, according to specific rules -
colour images can also be retrieved according to the meaning
they convey or to sensations they provoke.
• Light is energy, specifically electromagnetic
energy – eye (energy detector)
• The eye can distinguish between some
types of electromagnetic energy. Those
distinctions are seen as colours.
• The whiteness of an image area and the
amount of light hitting the eye
– The actual reflectance
– The brightness of incident light
– The incidence angle: the angle at which the light
hits the object (one per light source, and there
may be several)
– The surface orientation of the area with respect
to the viewer
"Colour is the visual effect that is caused by the spectral
composition of the light emitted, transmitted, or reflected
• What is texture?
• How to detect texture information?
• How to measure it?
• How to use it?
Shape and texture
• Together with colour, texture is a powerful
discriminating feature, present almost
everywhere in nature.
• Like colours, textures are connected with
psychological effects. In particular, they
emphasize orientations and spatial depth
between overlapping object.
• There are three standard problems to do with
– Texture segmentation is the problem of breaking an
image into components within which the texture is
constant. Texture segmentation involves both
representing a texture, and determining the basis on
which segment boundaries are to be determined. How
texture should be represented.
– texture synthesis seeks to construct large regions of
texture from small example images.
– Shape from texture involves recovering surface
orientation or surface shape from image texture.
Traditional Definition of Texture
• Texture refers to a spatially repeating pattern on
a surface that can be sensed visually
• In the image, the apparent size, shape, spacing
etc, of the texture elements (the texels) do
– Varying distances of the different texels from the
– Varying foreshortening of the different texels.
• texture gradients - systematic change in the
size and shape of the elements making up a
recover shape from texture
Recover Shape From Texture
• After some mathematical analysis , one can
compute expressions for the rate of change of
various image texel features, such as area,
foreshortening, and density. These texture
gradients are functions of the surface shape as
well as its slant and tilt with respect to the viewer.
• To recover shape from texture, one can use two-
– 1) measure the texture gradients
– 2) estimate the surface shape, slant, and tilt that
would give rise to the measured texture gradients.
Texture is a broad
term used in
patches (of any
size) that are
•Techniques to extract
image are many,
based on different
textures can be based
on statistical and
Texture Content Measurement
• Textures may be described according to their
spatial, frequency or perceptual properties.
Periodicity, coarseness, preferred direction, degree
of complexity are some of the most perceptually
salient attributes of a texture.
• Feature spaces based on these attributes are
particularly interesting for image retrieval by
Space – based models
• Auto-correlation function A texture can be
represented taking into account the spatial size of
grey-level primitives. Fine textures have a small
size of their grey-level primitives. Coarse
textures a large size.
• Co – occurrence matrix A different way of
measuring textures is by taking into account the
spatial arrangement of grey-level primitives.
• Define a relative separation vector
– e.g. 3 pixels across, 2 up
• Use each pair of pixels separated by the
vector as matrix indices
• Increment this matrix element
• Shape of matrix characterises the texture
• Can be characterised by factors derived
• Density of microedges is characteristic of
• Apply an edge detector
– Sobel is suitable
• Threshold result
• Compute density of edge elements