The importance of the perceived quality measurement is fundamental for many image processing applications, such as compression, acquisition, restoration, enhancement, and reproduction. Color information is also of great importance for the perceived image quality, although perceived information is mainly represented by luminance. We present a computational and memory-efficient no-reference image quality assessment model independent of JPEG and JPEG2000 coded color images based on local regions. We also present the discrimination algorithm for these two types of coded images. The features of local regions are blockiness around the block boundary, average absolute difference between adjacent pixels within the block, and zero crossing rate within the block of the image. We validate the performance of our model on our subjective database, which shows good quality prediction performance, and the model's generalization ability is also verified on the other database.