<![CDATA[The hospital pharmacy installation plays an essential role in ensuring the quality of pharmaceutical supplies. One important stage in drug production is raw material analysis, particularly melting point determination as a purity indicator. Conventional methods, such as capillary tubes, are limited in accuracy and prone to subjectivity. This study aims to develop an automated image-based monitoring system integrated with Hot Stage Microscopy (HSM) to objectively detect real-time morphological changes in pharmaceutical materials. The system was designed using digital image processing stages consisting of image acquisition, processing, and output. Images were captured using a binocular microscope and processed on an Odroid XU4 mini-computer. Phase boundaries were identified using the Active Contour segmentation method, while texture features were extracted using the Gray Level Co-occurrence Matrix (GLCM) at four orientation angles. Classification was performed using a Support Vector Machine (SVM) with a Radial Basis Function (RBF) kernel. The results showed that the Active Contour method effectively detected melting phases, and the SVM achieved an accuracy of 91.67%, precision of 91.89%, sensitivity of 91.67%, and an F1-score of 91.66%. The system successfully distinguished pure Paracetamol from mixtures with Gallic Acid and Ferulic Acid.]]>
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