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An Evaluation Measure of Image Segmentation Based on Object Centres

2006; Springer Science+Business Media; Linguagem: Inglês

10.1007/11867586_27

1611-3349

James Charles, Ludmila I. Kuncheva, B. Wells, Ik Soo Lim,

Image and Object Detection Techniques

Classification of organic materials obtained from rock and drill cuttings involves finding multiple objects in the image. This task is usually approached by segmentation. The quality of segmentation is evaluated by matching the whole detected objects to a reference segmentation. We are interested in representing each object by a single reference point called the “centre”. This paper proposes an evaluation measure of image segmentation for such representation. We argue that measures based only on distance between obtained centres and a set of predefined centres are insufficient. The proposed measure is based on a list of desirable properties of the segmentation. The three components of the measure evaluate the under/over segmentation of the objects, the proportion of centres placed in the background rather than in objects, and the distance between the guessed and the true centres. The ability of the measure to distinguish between segmentation results of different quality is illustrated on three sets of examples including an image containing microfossils and pieces of inert material.