Abstarct: Document layout analysis is one of the critical steps in converting a document image to its text. Separating textual and non-textual areas within an image and extracting lines containing text from textual regions is the most effective preprocessing possible in optical character recognition systems. Failure to correctly identify areas containing text and, consequently, incorrect recognition of line coordinates will disrupt all subsequent parts of an optical character recognition system. Problems such as curvature of lines, skewness of the image, presence of diacritics and many dots in Persian and Arabic, the proximity of lines within the image, and pictures with more than one column prevented previous works from achieving high accuracy in document formatting analysis systems. In this research, a new method for analyzing Persian document layout is presented. The proposed method uses several different ways and a voting system among them, extracts the textual areas of the image, and then uses the font size estimate to more accurately identify the lines, which has not been used in previous works. The proposed method is evaluated on a databaxse that contains more than 2000 images. In two sections of detecting areas containing text and extracting lines, the accuracy has reached 98.04% and 99.42%.