We propose a computational method for generating sequential kinoforms of real-existing full-color threedimensional (3D) objects and realizing high-quality 3D imaging. The depth map and color information are obtained using non-contact full-color 3D measurement system based on binocular vision. The obtained full-color 3D data are decomposed into multiple slices with RGB channels. Sequential kinoforms of each channel are calculated and reconstructed using a Fresnel-diffraction-based algorithm called the dynamicpseudorandom-phase tomographic computer holography (DPP-TCH). Color dispersion introduced by different wavelengths is well compensated by zero-padding operation in the red and green channels of object slices. Numerical reconstruction results show that the speckle noise and color-dispersion are well suppressed and that high-quality full-color holographic 3D imaging is feasible. The method is useful for improving the 3D image quality in holographic displays with pixelated phase-type spatial light modulators (SLMs).