<![CDATA[In oil quality monitoring, digital imagery has become an essential tool. With the advancement of technology, digital imagery can be used to visualize oil samples and perform analysis quickly and accurately. However, effective image processing techniques are needed to generate useful information from digital images. The main problem faced in fuel quality evaluation is the inaccuracy and inconsistency of manual methods. Manual methods often require expensive equipment and trained workers and are prone to human error. Therefore, a more efficient and accurate method is needed. Morphological and histogram techniques on digital images offer a potential solution to this problem. One of the common techniques used in image processing is morphological techniques, which involve mathematical operations on images to change or describe certain image features. This technique can help identify important structures and patterns in Ron 92 oil images, such as quality and cleanliness. In addition, histograms are helpful statistical tools in image analysis, which represent the distribution of pixel intensities in an image. Histogram analysis can provide insight into the distribution of pixel intensity values in an oil image, which is relevant to the quality and homogeneity of the oil.]]>
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