![]() In our first method, LHS is applied on the entire image. Then, local histograms and local histogram statistics are learned from normal lighting images. Specifically, we first apply a high-pass filter on a face image to filter the low frequency illumination. The proposed methods are able to significantly remove both the low and high frequency parts of illumination on face images, as well as enhance face features lying in the low frequency part. In this paper, we propose two methods based on Local Histogram Specification (LHS) to preprocess face images under varying lighting conditions. High frequency illumination and low frequency face features bring difficulties for most of the state-of-the-art face image preprocessors. ![]() In the case of more than two variables, graphical methods are not applicable. To check the uniqueness of the solution none can use graphical method. The state diagram method can also be used, for which one needs only plot every allowable pair (c, m) on a rectangular coordinate system. Thus, from (3 ,3) the transition to (1, 3) is possible (by sending two cannibals across in the boat), but the transition from (3, 3) to (3,1) is not allowable because it would result in disaster for the one missionary remaining on the left bank. One must be careful to use allowable states. ![]() The method of enumeration consists of constructing a tree diagram. If the missionaries on either side of the river, or in the boat, are outnumbered at any time by cannibals, dire consequences which may be guessed at will result. A boat is available that will hold at most two people, and that can be navigated by any combination of cannibals and missionaries involving one or two people. This chapter discusses the classical conundrum-that is, a group consisting of three cannibals and three edible missionaries seeks to cross a river. ![]()
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