Abstract  We analyze some spatial frequency-based features used for text region detection in natural scene images, and redefine the DCT-based feature. We employ Fisher’s discriminant analysis to improve the DCT-based feature and to achieve higher accuracy. An unsupervised thresholding method for discriminating text and non-text regions is introduced and tested as well. Experimental results show that a wide high frequency band, covering some lower-middle frequency components, is generally more suitable for scene text detection despite the original definition of the DCT-based feature.