Baseline detection is an important step for off-line handwriting recognition of many alphabets. However, it remains a difficult task in the case of varying and irregular handwriting, and sometimes requires script-specific adaptations. In this paper, we propose a new method for baseline detection that is script independent. Indeed, this method is based on the principle of the perceptive vision, which combines several points of view of the same word (from low to high resolution). We validate the genericity of our method by extracting the baseline on three scripts: Arabic, French, and Indian (Bangla), without any adaptation of parameter. We compare our results with other works on the Arabic IFN/ENIT database. Moreover, baseline extraction is often realized independently for each studied word. In this work, we also demonstrate how the use of knowledge on the initial context of the word (text line) significantly improves baseline extraction.