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The image/video quality is a key issue in security video systems. Therefore the objective image/video quality criteria are extensively studied. In this paper, the novel full reference objective metric for image quality assessment is proposed. This metric is based on FSIM. The ROI detection is embedded in order to improve the performance. For ROI estimation, the ground truth data together with two different algorithms were used and compared - The security and multimedia images from LIVE database were used for performance evaluation. The correlation between the objective and subjective tests of multimedia images was calculated using Pearson's and Spearman Rank Order Correlation Coefficient. For performance comparison the state-of-the-art full reference objective image quality metrics were used; PSNR, SSIM, MS-SSIM, VIF and FSIM. In our previous paper, the importance of demosaicing technique and ROI has been shown. This paper continues in this topic and implements new full reference objective metrics for the reconstructed image quality evaluation. The results reveal that the ROI controlled by bottom-up mechanism can be used for performance improvement.