Through a slight modification of conventional monochromatic correlation, we formulate a color correlation which is capable of spectral and spatial recognition. Expressing RGB (red, green and blue) images, which are commonly used, in a vector form, the color correlation is decomposed of 9 terms, 3 intraband and 6 interband. To reduce the calculation time, we introduce preprocessings; projection onto appropriate plane and vector in RGB color space. The former one enables us to recognize an object with taking into account its both shape and color, and the latter one improves the sharpness of the cross-correlation peak. We also show the effectiveness of the color correlation applied to a quantitative measurement of stomach's surface from stereo endoscopic pictures.