In this letter, we propose a new method to detect faces in color images based on the characterized convex regional relationship. We detect skin and hair likeness regions using the derived skin and hair color models and the convex skin likeness and hair likeness regions are adopted as the characteristic convex regions. Finally, human faces can be detected via their intersection relationship. The proposed algorithm can accomplish face detection in an image including not only single face but also multi-faces and also detect deformed faces efficiently. To validity the effectiveness of the proposed method, we make experiments with various cases.

In this paper, in order to control uncertain chaotic system, an adaptive fuzzy control (AFC) scheme is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno (T-S) fuzzy models. The proposed AFC scheme provides robust tracking of a desired signal for the T-S fuzzy systems with uncertain parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the chaotic state tracks the state of the stable reference model (SRM) asymptotically with time for any bounded reference input signal. The suggested AFC design technique is applied to control of a uncertain Lorenz system based on T-S fuzzy model such as stabilization, synchronization and chaotic model following control (CMFC).