Abstract
Bodies of freshwater act as home to many different types of organisms, including algae. These algae can cause harm when something called a harmful algal bloom takes place, and as such it is desired to classify algae in micro-image samples from the freshwater bodies before a bloom occurs. This paper presents a novel method for improving the quality of the algae micro-image and segmenting the algae in the micro-image, two of the steps involved in the automatic recognition and classification of algae in images. First, the algae image quality was improved through the use of the Retinex enhancement technique. Then, the algae in the improved quality image was segmented from the background using a support vector machine. Experimental results indicate that the detection rate of the proposed method is over 95%.
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