The shrunk dimension of electronic devices leads to more stringent requirement on process control and quality assurance of their fabrication. For instance, direct die-to-die bonding requires placement of solder bumps not on PCB but on the wafer itself. Such wafer solder bumps, which are much miniaturized from the counterparts on PCB, still need to have their heights meet the specification, or else the electrical connection could be compromised, or the dies be crushed, or even the manufacturing equipments be damaged. Yet the tiny size, typically tens of microns in diameter, and the textureless and mirror nature of the bumps pose great challenge to the 3D inspection process. This paper addresses how a large number of such wafer bumps could have their heights massively checked against the specification. We assume ball bumps in this work. We propose a novel inspection measure about the collection of bump heights that possesses these advantages: (1) it is sensitive to global and local disturbances to the bump heights, thus serving the bump height inspection purpose; (2) it is invariant to how individual bumps are locally displaced against one another on the substrate surface, thus enduring 2D displacement error in soldering the bumps onto the wafer substrate; and (3) it is largely invariant to how the wafer itself is globally positioned relative to the imaging system, thus having tolerance to repeatability error in wafer placement. This measure makes use of the mirror nature of the bumps, which used to cause difficulty in traditional inspection methods, to capture images of two planes. One contains the bump peaks and the other corresponds to the substrate. With the homography matrices of these two planes and fundamental matrix of the camera, we synthesize a matrix called Biplanar Disparity Matrix. This matrix can summarize the bumps' heights in a fast and direct way without going through explicit 3D reconstruction. We also present a design of the imaging and illumination setup that allows the measure to be revealed in two images, and how the inspection measure could be estimated from the image data so acquired. Both synthetic and real data experimental results are shown to illustrate the effectiveness of the proposed system.