Osheima, Sony
Study on the effect of thresholding enhancement for the classification of texture images - Vol.103(1), Feb - New York Springer 2022 - 29-37p.
This work presents a study on the effect of photometric enhancement for the classification of texture images. The work compares the performance of image classification before and after enhancement using weighted thresholding enhancement technique. Weighted thresholding enhancement techniques are implemented using arithmetic sequence as weights on chosen sets of images. The features are extracted from wavelet packet coefficients of the chosen images for classification purpose. The study of the proposed work reveals that the weighted thresholding enhancement techniques based on arithmetic sequence improves the performance of classification of texture images.
Humanities and Applied Sciences
Study on the effect of thresholding enhancement for the classification of texture images - Vol.103(1), Feb - New York Springer 2022 - 29-37p.
This work presents a study on the effect of photometric enhancement for the classification of texture images. The work compares the performance of image classification before and after enhancement using weighted thresholding enhancement technique. Weighted thresholding enhancement techniques are implemented using arithmetic sequence as weights on chosen sets of images. The features are extracted from wavelet packet coefficients of the chosen images for classification purpose. The study of the proposed work reveals that the weighted thresholding enhancement techniques based on arithmetic sequence improves the performance of classification of texture images.
Humanities and Applied Sciences