This paper presents subpixel measurements of 2 D object dimensions by a vision system. Dimension measurements require accurate edge detection which implies first, the definition of the object edge position in the corresponding image grey level transition and second, the use of appropriate edge detection operators. To define the edge position, the different steps of the object to image transformation were modelled. Neglecting optical aberrations, object boundaries characterized by sharp physical discontinuities are proved to correspond to points of inflexion in the image grey level transitions. The operators we developed to locate those points of inflexion with subpixel accuracy use regression, interpolation and filtering of the grey levels. Numerical simulations were performed to evaluate and compare the precision of these operators. Those techniques were then applied to real images. To improve accuracy, a shape model of the object border was fitted to extracted inflexion points. Therefore, the final precision of the measurement depends on both edge detection operators accuracy and noise elimination bv model fitting. The method was first tested on known width black stripes images. In this simple case, the border shape was modelled by a straight line. For the best operators, even using a few regression points, a width acuracy of one tenth of a pixel was obtained. This result is independent of the stripe orientation relative to the camera detectors. Last, previous techniques were used compute cornea thickness from slit lamp images. The cornea borders shape was modelled by splines. Results are discussed and compared to ultrasound oachvmeter measurements. Different factors causing precision loss are analyzed and remedies are proposed.