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The monitoring of blast furnace raceways can be tackled by either analyzing available plant data like pressure or flow rate data or by attaching cameras to the inspection glasses at the end of the blow pipes. Visual raceway monitoring is not new, but the rapid development of camera technology over the past two decades has opened new possibilities and the constantly decreasing prices of camera hardware now allow a complete camera equipment for all tuyeres of a blast furnace at moderate costs. In addition, increasing CPU power enables sophisticated online processing of tuyere video data at reasonable frame rates. While most studies published in literature focus on characterising the coal plume to obtain information about constant coal discharge and dispersion,3–7) this study is dedicated on the question how we can detect raceway blockages in a fully automated manner by digital image processing of tuyere camera images. However, this paper is not meant to be an extensive overview on image processing algorithms, nor will we present an ultimate solution for the purpose of blockage detection. It should be seen as a discussion of various aspects and difficulties to extract information from tuyere camera images. Even though the task of blockage Improving Blast Furnace Raceway Blockage Detection. Part 3: Visual Detection Based on Tuyere Camera Images