In medical applications, miniature surgical instruments such as needles, or electrodes are introduced into human body. The position of instrument in tissue can be estimated using 3D ultrasound. In previous publications, we introduced two novel algorithms for automatic electrode localization from 3D ultrasound images. The first method is based on the parallel integral projection (PIP) transform, a modification of the Radon transform. We showed that the axis of the electrode can be estimated from the maximum of PIP transformation. To accelerate search for the maximum, a hierarchical mesh-grid algorithm is implemented. In second method, the electrode axis is described by a cubic polynomial. The distribution of voxel intensities inside the electrode region is a priori estimated from acquired data. The model parameters are robustly estimated using the RANSAC estimator. In this paper, their performance in terms of accuracy is compared. A series of tests on numerical phantoms created with the FIELD II simulation program were performed to quantitatively evaluate the localization accuracy. We observed a decrease in accuracy when artificial noise was added to the input data. The algorithms were also tested on real ultrasound data of a cryogel phantom comprising metallic electrode