Abstract-This paper presents the method for the extraction of the lungs part from the other parts for the diagnostic of the lungs part. The proposed method is based on the calculation of the connected component and the centroid of the image. Connected Component labeling is used to label the each objects in the binarized image. After the labeling is done, centroid value is calculated for each object. The filing operation is applied which helps to extract the lungs part from the image retaining all the parts of the original lungs image. The whole process is explained in the following steps and experimental results shows it's significant.
This paper presents splitting and merging algorithm based on adaptive thresholding. The algorithm first divides the image into blocks, and then compares each block using the calculated thresholding value. The blocks which are same are merged using the certain threshold value and different blocks are split unless it satisfies the threshold value. When the block has been merged, maximum and minimum block sizes are determined then the average block size is determined. After the average block size is determined the average intensity and standard deviation of average block is calculated. The process of thresholding is applied to binarize the image. Finally, the experimental results show that the proposed method distinguishes clearly the background with text in the document image.
In this paper, the proposed method is recognized the hands using color information with input image of the camera. It controls the mouse pointer using recognized hands. In addition, specific commands with the mouse pointer is designed to perform. Most users felt uncomfortable since existing interaction multimedia systems depend on a particular external input devices such as pens and mouse However, the proposed method is to compensate for these shortcomings by hand without the external input devices. In experimental methods, hand areas and backgrounds are separated using color information obtaining image from camera. And coordinates of the mouse pointer is determined using coordinates of the center of a separate hand. The mouse pointer is located in pre-filled area using these coordinates, and the robot will move and execute with the command. In experimental results, the recognition of the proposed method is more accurate but is still sensitive to the change of color of light.
키워드손동작 인식, HCI, 핸드마우스, 영상처리
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