We developed a method for reconstructing tree crown volume from a set of eight photographs taken from the N, S, E, W, NE, NW, SE and SW. This photographic method of reconstruction includes three steps. First, canopy height and diameter are estimated from each image from the location of the topmost, rightmost and leftmost vegetated pixel; second, a rectangular bounding box around the tree is constructed from canopy dimensions derived in Step 1, and the bounding box is divided into an array of voxels; and third, each tree image is divided into a set of picture zones. The gap fraction of each picture zone is calculated from image processing. A vegetated picture zone corresponds to a gap fraction of less than 1. Each picture zone corresponds to a beam direction from the camera to the target tree, the equation of which is computed from the zone location on the picture and the camera parameters. For each vegetated picture zone, the ray-box intersection algorithm (Glassner 1989) is used to compute the sequence of voxels intersected by the beam. After processing all vegetated zones, voxels that have not been intersected by any beam are presumed to be empty and are removed from the bounding box. The estimation of crown volume can be refined by combining several photographs from different view angles. The method has been implemented in a software package called Tree Analyzer written in C++. The photographic method was tested with three-dimensional (3D) digitized plants of walnut, peach, mango and olive. The 3D-digitized plants were used to estimate crown volume directly and generate virtual perspective photographs with POV-Ray Version 3.5 (Persistence of Vision Development Team). The locations and view angles of the camera were manually controlled by input parameters. Good agreement between measured data and values inferred from the photographic method were found for canopy height, diameter and volume. The effects of voxel size, size of picture zoning, location of camera and number of pictures were also examined.