Abstract:The extraction of information of standing tree images provides a fast and precise way for management of the forest resource inventory, also provides an important basis for pre-harvest assessment. Methods are proposed in this paper to acquire images of standing trees in real-time, to extract relevant features and to achieve fast recognition without destruction. Thus the rich information can be easily preserved and accessed based on intuition. So it provides a basis for the automation of a forest resource inventory management system, and at the same time, for the improvement of the traditional methods in the forest resource inventory and technology, which also reduces the labor intensity in field investigations. A tree measurement system is proposed to achieve the automatic and precise management of forest resources survey, as an enhancement of the traditional survey methods and techniques. A method of extracting the calibration stick by color components is proposed. First, using a tripod to keep the camera in the horizontal plane, i.e. to make sure that the imaging plane is parallel to the middle curve of the stem volume and normal to the ground. The images of the standing tree can thus be taken. Then a region growth algorithm is applied to search the tree contour. Region growth approach is adopted to achieve the image segmentation, where neighboring pixels are examined and different choices of seeds may have different segmentation results. According to the shape characteristics of the tree trunk, a seed pixel is chosen from the stem base. Then the main trunk is extracted by mathematical morphology. Finally the information of the diameter at the breast height, the diameter of the main branch and the branch height are determined according to photogrammetry and the parameters of the calibration stick. Experimental results show that these methods can effectively segment the calibration stick and the tree contour. It is convenient to obtain accurately and automatically the standing tree information.