[[abstract]]The gabor filter approach is recently used in texture analysis. Among the existing applications, people convolve the given texture image with a set of gabor filters with some user-specified parameters. The convolution takes a lot of time because of the large image size and the computational complexity. This paper utilizes the concept of multi-resolution with parameter selection to do texture analysis. The computation time can be significantly reduced by diminishing the image size according to several different sets of parameters. Experiments demonstrate that our strategy is quite efficient compared with the traditional gabor filter.[[fileno]]2030217010015[[department]]資訊工程學
Gabor filter is widely used to extract texture features from images for image retrieval. A number of...
Texture segmentation is one of the most important feature utilized in practical diagnosis because it...
The performance of a number of texture feature operators is evaluated. The features are all based on...
This paper presents a method for the design of multiple Gabor filters for segmenting multi-textured ...
Spatial-frequency methods have been extensively and successfully employed by many computer vision re...
[[abstract]]Gabor transform has recently been exploited to do texture analysis, including texture ed...
The focus of this thesis is on the development of texture segmentation algorithm. The texture featu...
We propose a new texture synthesis-by-analysis method inspired by current models of biological early...
Gabor filtering is a widely adopted technique for texture analysis. The design of a Gabor filter ban...
The paper introduces a new method of texture segmentation efficiency evaluation. One of the well kno...
In this correspondence, we propose a novel method for efficient image analysis that uses tuned match...
Gabor features are a common choice for texture analysis. There are several pop-ular sets of Gabor fi...
Receptive field profiles of simple cells in the visual cortex have been shown to resemble even- symm...
The paper introduces a new method of texture segmentation efficiency evaluation. One of the well kno...
Abstract. The paper introduces a new method of texture segmentation efficiency evaluation. One of th...
Gabor filter is widely used to extract texture features from images for image retrieval. A number of...
Texture segmentation is one of the most important feature utilized in practical diagnosis because it...
The performance of a number of texture feature operators is evaluated. The features are all based on...
This paper presents a method for the design of multiple Gabor filters for segmenting multi-textured ...
Spatial-frequency methods have been extensively and successfully employed by many computer vision re...
[[abstract]]Gabor transform has recently been exploited to do texture analysis, including texture ed...
The focus of this thesis is on the development of texture segmentation algorithm. The texture featu...
We propose a new texture synthesis-by-analysis method inspired by current models of biological early...
Gabor filtering is a widely adopted technique for texture analysis. The design of a Gabor filter ban...
The paper introduces a new method of texture segmentation efficiency evaluation. One of the well kno...
In this correspondence, we propose a novel method for efficient image analysis that uses tuned match...
Gabor features are a common choice for texture analysis. There are several pop-ular sets of Gabor fi...
Receptive field profiles of simple cells in the visual cortex have been shown to resemble even- symm...
The paper introduces a new method of texture segmentation efficiency evaluation. One of the well kno...
Abstract. The paper introduces a new method of texture segmentation efficiency evaluation. One of th...
Gabor filter is widely used to extract texture features from images for image retrieval. A number of...
Texture segmentation is one of the most important feature utilized in practical diagnosis because it...
The performance of a number of texture feature operators is evaluated. The features are all based on...