In this study, we propose an ellipse detection method which gives prospering results on occlusive cases. The method starts with detection of edge segments. Then we extract elliptical arcs by computing corners and fitting ellipse to the pixels between two consecutive corners. Once the elliptical arcs are extracted, we aim to test all possible arc subsets. However, this requires exponential complexity and runtime diverges as the number of arcs increases. To accelerate the process, arc pairing strategy is deployed by using conic properties of arcs. If any pair found to be non-coelliptic, then arc combinations including that pair are eliminated. Therefore the number of possible arcs subsets is reduced and computation time is improved. In the end, ellipse fitting is applied to remaining arc combinations to decide on final ellipses. Performance of the proposed algorithm is tested on real datasets, and better results have been obtained compare to state-of-the-art algorithms.