A practical skin color and texture

A practical skin color and texture analysis/synthesis
technique is introduced for this E-cosmetic function. Shading
on the face is removed by a simple color vector analysis in
the optical density domain as an inverse lighting technique.
The image without shading is analyzed by a previously
introduced technique that extracts hemoglobin and melanin
components by independent component analysis. The
comparison shows an excellent match between the
synthesized and actual images of changes due to tanning and
alcohol consumption. We also proposed a technique to
synthesize the change of texture in pigment due to aging or
the application of cosmetics. [1]
Grain size and anisotropy are evaluated with proper
diagrams. The possibility to determine the presence of
pattern defects is also discussed. [2]
The skin color image is decomposed to the four texture
components by multi-resolution analysis using wavelet
transform. A variety of skin images with different conditions
of skin color and texture are created in a linear combination
of the texture components. Experimental results show good
separation of skin textures by wavelet analysis and realistic
synthesized images. [3]
To make improvement in this regard, we propose a new
texture analysis synthesis framework that combines two
main ideas. Firstly, in material space we decompose the
texture contents into units with "basic shape" and 'feature
vector ". Based on this, the space spanned by a set of
sampled textons is constructed to help introduce additional
changes upon textons. Secondly, in pattern space, using the
idea of 'feature texture “acquired from texture swatch for
different properties especially for distribution rules of
textons, we may capture and manipulate the global structure
flexibly. By this formulization, we are able to obtain

ผลลัพธ์ (อังกฤษ) 2:

A Practical Skin color and texture analysis / synthesis
Technique is introduced for this E-Cosmetic function. Shading
on The Face is removed by a Simple color vector analysis in
The Domain Optical density As an inverse Lighting Technique.
The Image Without shading is analyzed by a previously
introduced Technique that extracts hemoglobin and melanin
components by independent Component analysis. The
comparison Shows an excellent Match between The
synthesized and Actual images of Changes Due to Tanning and
Alcohol consumption. We also proposed a Technique to
Synthesize The Change of texture in Pigment Due to Aging or
The Application of Cosmetics. [1]
Grain size and anisotropy are evaluated with Proper
diagrams. The possibility to Determine The Presence of
pattern defects is also discussed. [2]
The Skin color Image is decomposed to The Four texture
components by Multi-resolution analysis using wavelet
transform. A Variety of Skin images with different conditions
of Skin color and texture are Created in a Linear Combination
of The texture components. Experimental results show good
Separation of Skin Textures by wavelet analysis and realistic
synthesized images. [3]
To Make Improvement in this Regard, we Propose a New
Framework texture synthesis analysis that Combines Two
main Ideas. Firstly, in Material Space we decompose The
texture contents Into units with "Basic Shape" and 'Feature
vector ". Based on this, The Space spanned by a Set of
sampled Textons is constructed to Help introduce Additional
Changes upon Textons. Secondly, in pattern. Space, using The
idea of 'Feature texture "acquired from SWATCH texture for
different Properties especially for Distribution Rules of
Textons, May we Capture and Manipulate The Global structure
flexibly. By this Formulization, we are Able to Obtain.

ผลลัพธ์ (อังกฤษ) 3:

A practical skin color and texture analysis / synthesis
technique is introduced for this E-cosmetic function. Shading
on. The face is removed by a simple color vector analysis in
the optical density domain as an inverse lighting technique.
The. Image without shading is analyzed by a previously
introduced technique that extracts hemoglobin and melanin
components by. Independent component analysis. The
.Comparison shows an excellent match between the
synthesized and actual images of changes due to tanning and
alcohol, consumption. We also proposed a technique to
synthesize the change of texture in pigment due to aging or
the application of, cosmetics. [1]
Grain size and anisotropy are evaluated with proper
diagrams. The possibility to determine the presence of
pattern defects. Is also discussed.[2]
The skin color image is decomposed to the four texture
components by multi-resolution analysis using wavelet
transform.? A variety of skin images with different conditions
of skin color and texture are created in a linear combination
of the. Texture components. Experimental results show good
separation of skin textures by wavelet analysis and realistic
synthesized. Images. [3]
.To make improvement in this regard we propose, a new
texture analysis synthesis framework that combines two
main, ideas. Firstly in material, space we decompose the
texture contents into units with "basic shape" and 'feature
vector. "Based. On this the space, spanned by a set of
sampled textons is constructed to help introduce additional
changes upon, textons. Secondly in space using, pattern, the
.Idea of 'feature texture "acquired from texture swatch for
different properties especially for distribution rules of
textons,, We may capture and manipulate the global structure
flexibly. By, this formulization we are able to obtain.