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Tree trunk diameter is one of the most important tree measuring factors in forest inventory. To quickly and accurately measure the tree trunk, electronic components were applied for tree trunk image recognition and measurement. Application of image processing technology in forest mensuration proposes a solution for accurately measuring trees, which makes nonprofessional technicians measure trees easily without experience. Images were taken by camera and processed by CMOS. The image was smoothed by Gaussian inverse filter after conversion from RGB to greyscale. Then edge was detected through nonmaximum suppression and double thresholds edge connection. Tree trunk automatic detection algorithm was developed on the base of the detecting image. The algorithm used a 4column window that represented a vertical segment to extract the vertical segments from the images above. The algorithm got rid of the vertical segment with over two successive 0 values, including vertical, horizontal and diagonal directions. The detected 0 value was searched from top to bottom. In addition, individual points in the window were removed. When all the vertical lines were abstracted, the two vertical lines with the maximum width were represented as the tree trunk. Tree trunk diameter was computed according to the relationship among focal length, object distance, image distance and pixel size. The image recognition results were validated by selecting different trees. Results showed that the image recognition precision was 96.9% and most data were conformed to the requirement of forest inventory. The forestry intelligence was explored and the digitizing components was used to realize the forestry intelligence.