This paper presents a novel color separation method for Hematoxylin-Eosin (H&amp;E) stained Histopathology Images. The whole (<i>R;G;B</i>) space of the input image is projected to a family of surfaces connecting the distributions of a series of [<i>(R + B)²=B;G</i>] planes that divide the cloud of H&amp;E tones. Such projection is then used to cluster both the Hematoxylin and Eosin samples, from where the color basis are then derived. The projection presented herein is more resilient to noise and therefore the separation process is less hampered when the staining properties largely vary. Unlike other normalization methods evaluated by comparing with gold standard images, the power of the method was demonstrated by thresholding the resulting Hematoxylin image with the well-known Otsu's method and the number of detected nuclei was compared with two manually annotated datasets. Despite the simplicity of this approach, the detection sensitivity was 71 % and 67 %, respectively