A new method is presented for the segmentation of pulmonary parenchyma. The proposed method is based on the area calculation of different objects in the image. The main purpose of the proposed algorithm is the segment...A new method is presented for the segmentation of pulmonary parenchyma. The proposed method is based on the area calculation of different objects in the image. The main purpose of the proposed algorithm is the segment of the lungs images from the computer tomography(CT) images. The original image is binarized using the bit-plane slicing technique and among the different images the best binarized image is chosen. After binarization, the labeling is done and the area of each label is calculated from which the next level of binarized image is obtained. Then, the boundary tracing algorithm is applied to get another level of binarized image. The proposed method is able to extract lung region from the original images. The experimental results show the significance of the proposed method.展开更多
This paper presents a new method for text detection, location and binarization from natural scenes. Several morphological steps are used to detect the general position of the text, including English, Chinese and Japan...This paper presents a new method for text detection, location and binarization from natural scenes. Several morphological steps are used to detect the general position of the text, including English, Chinese and Japanese characters. Next bonnding boxes are processed by a new “Expand, Break and Merge” （EBM） method to get the precise text areas. Finally, text is binarized by a hybrid method based on Otsu and Niblack. This new approach can extract different kinds of text from complicated natural scenes. It is insensitive to noise, distortedness, and text orientation. It also has good performance on extracting texts in various sizes.展开更多
基金supported (in part) by research funding from Chosun University, Korea, 2013
文摘A new method is presented for the segmentation of pulmonary parenchyma. The proposed method is based on the area calculation of different objects in the image. The main purpose of the proposed algorithm is the segment of the lungs images from the computer tomography(CT) images. The original image is binarized using the bit-plane slicing technique and among the different images the best binarized image is chosen. After binarization, the labeling is done and the area of each label is calculated from which the next level of binarized image is obtained. Then, the boundary tracing algorithm is applied to get another level of binarized image. The proposed method is able to extract lung region from the original images. The experimental results show the significance of the proposed method.
文摘This paper presents a new method for text detection, location and binarization from natural scenes. Several morphological steps are used to detect the general position of the text, including English, Chinese and Japanese characters. Next bonnding boxes are processed by a new “Expand, Break and Merge” （EBM） method to get the precise text areas. Finally, text is binarized by a hybrid method based on Otsu and Niblack. This new approach can extract different kinds of text from complicated natural scenes. It is insensitive to noise, distortedness, and text orientation. It also has good performance on extracting texts in various sizes.
