The objective of the research study was to determine the possibility of using computer vision systems (CVS) to detect a PSE defect in pork meat. The research material comprised 42 pork longissimus dorsi muscles obtained under the industrial conditions. Based on the measurements of pH and colour lightness (L*), the raw material studied was classified into three quality groups: normal meat (RFN, i.e. reddishpink, firm, non-exudative), PSE meat (pale, soft, exudative), and meat that did not meet any criteria of being classified into any of the two quality groups as above (NZ). The meat samples analyzed were photographed and their images were analyzed in order to determine the values of colour components of the three models: RGB, HSV, and HSL. Based on the results obtained, it was found that CVS could be applied to detect a PSE defect in pork meat. For this purpose, the colour components of V (from the HSV model), L (from the HSL model), and R, G, B (from the RGB model) appeared to be most useful.