The objective of this research was to develop an image analysis technique for severity rating of brown leaf spot disease in cassava. Samples of cassava leaves were collected from field and imaged under controlled illumination. Images resolution were resized to 640×480 pixels and transformed from RGB to HSI color space. The transformed images were then segmented and feature-extracted in order to determine total leaf area and diseased area. Noise reduction was performed using erosion and dilation procedure. The percentage of inflection was calculated based on diseased area and total leaf area. Comparative assessment by manual scoring based on conventional illustrated diagram key was conducted. The results showed a good agreement between the number of spot counts obtained by manual scoring and by image analysis at an R2=0.90, but with greater standard diviation for manual scoring. The number of spots was found to affect the accuracy of image analysis.