Text based pictures called text art are often used in Web pages, email text and so on. They delight us, but they can be noise for handling the text data. For example, they can be obstacle for text-to-speech software and natural language processing. Such problems will be solved by text art extraction methods which detects the area of text art in a given text data, and text art extraction methods can be constructed by text art recognition methods which tell if a given fragment of text data is a text art or not. Previous works for text art recognition methods assume that a specific natural language is used in text data, and do not work for text data with other natural languages well. In this paper, we propose a text art extraction method for multi natural languages. Attributes of a given text data which our method uses include how the text data looks like text art while attributes of it which the previous works use include how the text data looks like a natural language text. Our experiment shows that our method works well for both English text and Japanese text data.