The current challenge in biomedical research is to detect genetic risk factors involved in common complex diseases. The power to detect their role is generally poor in populations that have been large for a long time. It has been suggested that the power may be increased by taking advantage of the specificity of founder populations; linkage disequilibrium spanning larger regions and kinship coefficients being stronger than in large populations. A new method is proposed here, the Maximum Identity Length Contrast (MILC) which, in contrast with other existing methods, does not make the assumption of unique ancestry for the genetic risk factors. It is thus appropriate for a search for common genetic risk factors for complex diseases. Statistical properties of the method are discussed in realistic contexts.