Xitao Zheng

Work place: College of IT, Shanghai Ocean University, Shanghai 201306, China

E-mail: xtzheng@shou.edu.cn


Research Interests:


Author Articles
Recognition of Marrow Cell Images Based on Fuzzy Clustering

By Xitao Zheng Yongwei Zhang Yehua Yu Jing Zhang Jun Shi

DOI: https://doi.org/10.5815/ijitcs.2012.01.06, Pub. Date: 8 Feb. 2012

In order to explore the leukocyte distribution of human being to predict the recurrent leukemia, the mouse marrow cells are investigated to get the possible indication of the recurrence. This paper uses the C-mean fuzzy clustering recognition method to identify cells from sliced mouse marrow image. In our image processing, red cells, leukocytes, megakaryocyte, and cytoplasm can not be separated by their staining color, RGB combinations are used to classify the image into 8 sectors so that the searching area can be matched with these sectors. The gray value distribution and the texture patterns are used to construct membership function. Previous work on this project involves the recognition using pixel distribution and probability lays the background of data processing and preprocessing. Constraints based on size, pixel distribution, and grayscale pattern are used for the successful counting of individual cells. Tests show that this shape, pattern and color based method can reach satisfied counting under similar illumination condition.

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The Obstacle Detection and Measurement Based on Machine Vision

By Xitao Zheng Shiming Wang Yongwei Zhang

DOI: https://doi.org/10.5815/ijisa.2010.02.03, Pub. Date: 8 Dec. 2010

To develop a quick obstacle detection and measurement algorithm for the image-based autonomous vehicle (AV) or computer assisted driving system, this paper utilize the previous work of object detection to get the position of an obstacle and refocus windows on the selected target. Further calculation based on single camera will give the detailed measurement of the object, like the height, the distance to the vehicle, and possibly the width. It adopts a two camera system with different pitch angles, which can perform real-time monitoring for the front area of the vehicle with different coverage. This paper assumes that the vehicle will move at an even speed on a flat road, cameras will sample images at a given rate and the images will be analyzed simultaneously. Focus will be on the virtual window area of the image which is proved to be related to the distance to the object and speed of the vehicle. Counting of the blackened virtual sub-area can quickly find the existence of an obstacle and the obstacle area will be cut to get the interested parameter measurements for the object evaluation.

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