The rich and colorful leather design brings a broad stage of fashion design in the past, China＇s leather （leather） clothing brand single, old style, color： black, blue, is brown. The economic and cultural developm...The rich and colorful leather design brings a broad stage of fashion design in the past, China＇s leather （leather） clothing brand single, old style, color： black, blue, is brown. The economic and cultural development, leading the fashion changes, the concept is also constantly promote the development of a new direction, to the consumer, aesthetic with the change of consumption concept, the fur （leather） apparel consumption presents a civilian, personalized, ideal trend, leather （leather） clothing to reflects personal charm and style of the clothing style, design aesthetic appreciation, knowledge and other aspects of the new technology and new materials to absorb human body art is to stimulate leather （leather） the change of clothing. With the continuous development of science and technology, intelligent garment customization to the majority of consumers, the effect of intelligent custom fur （leather） three direction costumes （fabrics, colors, styles） for innovative research, get a Of leather （leather） costumes to break the current leather （leather） styles of dull shape, rich leather （leather） and other clothing charm, for the fur （leather） costumes to all ages personality need to provide ideas and new development space.展开更多
In the process of clothing image researching,how to segment the clothing quickly and accurately and retain the clothing style details as much as possible is the basis of subsequent image analysis.Spectral clustering c...In the process of clothing image researching,how to segment the clothing quickly and accurately and retain the clothing style details as much as possible is the basis of subsequent image analysis.Spectral clustering clothing image segmentation algorithm is a common method in the process of clothing image extraction.However,the traditional model requires high computing power and is easily affected by the initial center of clustering.It often falls into local optimization.Aiming at the above two points,an improved spectral clustering clothing image segmentation algorithm is proposed in this paper.The Nystrom approximation strategy is introduced into the spectral mapping process to reduce the computational complexity.In the clustering stage,this algorithm uses the global optimization advantage of the particle swarm optimization algorithm and selects the sparrow search algorithm to search the optimal initial clustering point,to effectively avoid the occurrence of local optimization.In the end,the effectiveness of this algorithm is verified on clothing images in each environment.展开更多
文摘The rich and colorful leather design brings a broad stage of fashion design in the past, China＇s leather （leather） clothing brand single, old style, color： black, blue, is brown. The economic and cultural development, leading the fashion changes, the concept is also constantly promote the development of a new direction, to the consumer, aesthetic with the change of consumption concept, the fur （leather） apparel consumption presents a civilian, personalized, ideal trend, leather （leather） clothing to reflects personal charm and style of the clothing style, design aesthetic appreciation, knowledge and other aspects of the new technology and new materials to absorb human body art is to stimulate leather （leather） the change of clothing. With the continuous development of science and technology, intelligent garment customization to the majority of consumers, the effect of intelligent custom fur （leather） three direction costumes （fabrics, colors, styles） for innovative research, get a Of leather （leather） costumes to break the current leather （leather） styles of dull shape, rich leather （leather） and other clothing charm, for the fur （leather） costumes to all ages personality need to provide ideas and new development space.
文摘In the process of clothing image researching,how to segment the clothing quickly and accurately and retain the clothing style details as much as possible is the basis of subsequent image analysis.Spectral clustering clothing image segmentation algorithm is a common method in the process of clothing image extraction.However,the traditional model requires high computing power and is easily affected by the initial center of clustering.It often falls into local optimization.Aiming at the above two points,an improved spectral clustering clothing image segmentation algorithm is proposed in this paper.The Nystrom approximation strategy is introduced into the spectral mapping process to reduce the computational complexity.In the clustering stage,this algorithm uses the global optimization advantage of the particle swarm optimization algorithm and selects the sparrow search algorithm to search the optimal initial clustering point,to effectively avoid the occurrence of local optimization.In the end,the effectiveness of this algorithm is verified on clothing images in each environment.
