Abstract:
Disclosed are a method and a system that could adaptively improve the visual quality of people with low-vision impairment, regardless of network and terminal. The low-vision impairment is described by a set of "symptoms" that is semantically defined. As the description tool of low vision impairments, it is flexible and reliable to use the proposed "symptoms" based descriptions rather than individually identified names of eye disease, because the user can describe his/her low-vision impairment by specifying associated symptoms based on his/her own experience. The inputted visual contents are adaptively transformed according to the low vision-impairment.
Abstract:
Disclosed are a method and a system that adaptively transform visual contents inputted from a network, in accordance with the visual characteristics of a terminal user. A visual characteristics descriptor that describes the information of the user visual characteristics in a predetermined format is proposed. The descriptor includes the information of the color vision deficiency type and the color vision deficiency degree. The color vision deficiency may be described in numerical degree or textual degree. The invention adaptively transforms visual contents differently in accordance with the color vision deficiency type.
Abstract:
A texture description method in a frequency domain for extracting texture features by transforming and Gabor-filtering an input image into an image of the frequency domain, and a texture-based retrieval method thereof are provided. The texture description method in the frequency domain includes: a first step of transforming an image of a time domain into an image of the frequency domain; a second step of filtering the transformed image using a Gabor filter having NxM filter regions, where N and M are respective predetermined positive integers; a third step of extracting feature values of the image that has been Gabor-filtered in respective channels of the frequency domain division layout corresponding to the NxM filter regions of the Gabor filter; and a fourth step of deciding a texture descriptor of the image on the basis of the feature values of the image.
Abstract:
A texture description method using a Gabor filter in a frequency domain for describing texture information of an image, comprises: a first step of converting an image, in which an image of a time domain is transformed into an image of a frequency domain; a second step of filtering the transformed image of the frequency domain using a Gabor filter having N*M filtering regions, where N and M are predetermined positive integers; a third step of extracting feature values of the Gabor-filter image in respective channels of a frequency domain division layout corresponding to the N*M filter regions of the Gabor filter; and a fourth step of describing the image texture descriptor using the texture feature values of the image.
Abstract:
A texture description method in a frequency domain for extracting texture features by transforming and Gabor-filtering an input image into an image of the frequency domain, and a texture-based retrieval method thereof are provided. The texture description method in the frequency domain includes: a first step of transforming an image of a time domain into an image of the frequency domain; a second step of filtering the transformed image using a Gabor filter having NxM filter regions, where N and M are respective predetermined positive integers; a third step of extracting feature values of the image that has been Gabor-filtered in respective channels of the frequency domain division layout corresponding to the NxM filter regions of the Gabor filter; and a fourth step of deciding a texture descriptor of the image on the basis of the feature values of the image.
Abstract:
A texture description method in a frequency domain for extracting texture features by transforming and Gabor-filtering an input image into an image of the frequency domain, and a texture-based retrieval method thereof are provided. The texture description method in the frequency domain includes: a first step of transforming an image of a time domain into an image of the frequency domain; a second step of filtering the transformed image using a Gabor filter having N x M filter regions, where N and M are respective predetermined positive integers; a third step of extracting feature values o f the image that has been Gabor-filtered in respective channels of the frequen cy domain division layout corresponding to the N x M filter regions of the Gabo r filter; and a fourth step of deciding a texture descriptor of the image on t he basis of the feature values of the image.
Abstract:
Disclosed are a method and a system that could adaptively improve the visual quality of people with low-vision impairment, regardless of network and terminal. The low-vision impairment is described by a set of "symptoms" that is semantically defined. As the description tool of low vision impairments, it is flexible and reliable to use the proposed "symptoms" based descriptions rather than individually identified names of eye disease, because the user can describe his/her low-vision impairment by specifying associated symptoms based on his/her own experience. The inputted visual contents are adaptively transformed according to the low vision-impairment.
Abstract:
Disclosed are a method and a system that adaptively transform visual contents inputted from a network, in accordance with the visual characteristics of a terminal user. A visual characteristics descriptor that describes the information of the user visual characteristics in a predetermined format is proposed. The descriptor includes the information of the color vision deficiency type and the color vision deficiency degree. The color vision deficiency may be described in numerical degree or textual degree. The invention adaptively transforms visual contents differently in accordance with the color vision deficiency type.
Abstract:
A texture description method in a frequency domain for extracting texture features by transforming and Gabor-filtering an input image into an image of the frequency domain, and a texture-based retrieval method thereof are provided. The texture description method in the frequency domain includes: a first step of transforming an image of a time domain into an image of the frequency domain; a second step of filtering the transformed image using a Gabor filter having N x M filter regions, where N and M are respective predetermined positive integers; a third step of extracting feature values o f the image that has been Gabor-filtered in respective channels of the frequen cy domain division layout corresponding to the N x M filter regions of the Gabo r filter; and a fourth step of deciding a texture descriptor of the image on t he basis of the feature values of the image.