Utilizing sophisticated image processing techniques within the framework of palaeography has garnered increasing attention recently, giving rise to a new area of study sometimes referred to as "computerized palaeography". Both example acknowledgment and highlight extraction procedures, which provide quantitative arguments to support master derivations, are important in this subject. In this work, we provide an example acknowledgment structure that aims to address a common palaeographic problem: identifying the various copyists who have collaborated on the documentation of a single middle-aged book. In the case of a highly standardized book typology (the purported Latin "Monster Bible"), we wanted to see if extracting any deliberately artificial highlights related to page format would yield results that were acceptable. To this point, we have additionally played out a measurable examination of the considered highlights to describe their discriminant power. The tests, performed on an enormous dataset of advanced pictures from the alleged "Avila Bible" - a monster Latin duplicate of the entire Thus far, we have also conducted a quantifiable analysis of the highlights under consideration in order to characterize their discriminant potential. Experiments conducted using a massive dataset of sophisticated images from the so-called "Avila Bible"—a massive Latin copy of the complete Bible distributed between Italy and Spain in the 18th century—verified the optional nature of the suggested method. Bibles distributed in Italy and Spain in the 18th century attested to the elective nature of the suggested method.