Pencil Drawing of Microscopic Images Through Edge Preserving Filtering

Abstract

Automatic diatom identification approaches have revealed remarkable abilities to tackle the challenges of water quality assessment and other environmental issues. Scientists often analyze the taxonomic characters of the target taxa for automatic identification. In this process the digital photographs, sketches or drawings are recorded to analyze the shape and size of the frustule, the arrangement of striae, the raphe end- ings, and the striae density. In this paper, we describe two new methods for producing drawings of different diatom species at any stage of their life cycle development that can also be useful for future reference and comparisons. We attempt to produce drawings of diatom species using Edge-preserving Multi-scale Decomposition (EMD). The edge preserv- ing smoothing property of Weighted Least Squares (WLS) optimization framework is used to extract high-frequency details. The details extracted from two-scale decomposition are transformed to drawings which help in identifying possible striae patterns from diatom images. To analyze the salient local features preserved in the drawings, the Scale Invari- ant Feature Transform (SIFT) model is adopted for feature extraction. The generated drawings help to identify certain unique taxonomic and morphological features that are necessary for the identification of the diatoms. The new methods have been compared with two alternative pencil drawing techniques showing better performance for details preservation.