Flat panel displays have been used in a wide range of electronic devices. The defects on their surfaces are an important factor affecting the product quality. Automated optical inspection (AOI) method is an important and effective means to perform the surface defection inspection. In this paper, a kind of defect extraction algorithm based on one dimensional (1D) Fourier theory for the surface defect extraction with periodic texture background is introduced. In the algorithm, the scanned surface images are firstly transformed from time domain to frequency domain by 1D Fourier transform. The periodic texture background on the surface is then removed by using filtering methods in the frequency domain. Then, a dual-threshold statistical control method is applied to separate the defects from the surface background. Traditional 1D Fourier transform scheme for detecting ordinary defects is very effective; however, the method is not where the defect direction is close to horizontal in periodic texture background. In order to tackle the problem, a mean threshold method based on faultless image is put forward. It firstly calculates the upper and lower control limits of the every reconstructed line scanned image with faultless and then computes the averages of the upper and lower limits. The averages then act as the constant double thresholds to extract the defects. The experimental results of different defects show that the method developed in the paper is very effective for TFT-LCD panel surface defect inspection even in the circumstance that the defect directions are close to horizontal.