Implicit polynomials (IPs) are among the most effective representations for modeling and recognition of complex geometric shape structures because of their stability, robustness and invariant characteristics. In this paper, me describe an approach for geometric indexing into pictorial databases using implicit polynomial representations. We discuss in detail a breakthrough in invariant decomposition of a complex object shape into manageable pieces or patches. The self and mutual invariants of those invariant patches can be then used as geometric indexing feature vectors. The new concept of invariant signature curve for complex shapes is developed that captures the semi-global algebraic structure of the object and has the advantage of being able to deal with multi-scale and object occlusion.