Contrast and Brightness are two major factors, which affect the superiority of an image for easy or stainless or pleasant viewing. Overall lighting condition and darkness condition of the image collectively called as brightness, whereas differences in brightness or intensity range between the low and high-intensity value of an image are called as contrast. Histogram equalization is a very famous approach for image contrast adjustment or enhancement in image processing, but which produces sometimes washed out appearance, especially for a small region of the grayscale image. Contrast adjustment is part of the noise filtering or smoothing process, which is essential in automatic identification or recognition systems like a fingerprint or any other biometric-based recognition systems to get higher efficiency. Histogram-based equalization is simple in terms understandability and implementation, which is referred as one of the greatest advantages of this contrast adjustment method. Histogram equalization is less expensive compared to another similar type of contrast adjustment or enhancement algorithm. The novel approach planned in this paper controls dominating gray levels before applying histogram equalization process so that it performs enhancement of the image without over brightness or over darkness, which makes smaller part of the image invisible or loss of details in that portion of the image. This method outperforms histogram equalization method by enhancing the contrast with intermediate brightness or neither too bright nor too dark. In this paper, we compare different types of the grayscale image using the novel method and global histogram equalization method using MATLAB.