A Survey on Performance Evaluation of Object Detection Techniques in Digital Image Processing
In digital image processing , the performance evaluation means the analysis of parameters that improves the execution of the proposed system there by producing the optimized result. The image is defined as a Scene consists of objects of interest. To understand the contents of the image , one should know the objects that are located in the image. The shape of the object is a binary image representing the extent of the object. In Digital Image processing the shapes are represented and described in various methods .Shape representation method results in a non numeric representation of the original shape (e.g.) a graph. So that the important characteristics of the shape are preserved. The shape description refers to the methods that result in a numeric descriptor of the shape and is a step subsequent to shape representation .Skeletons are one such shape descriptors. The skeleton of a two-dimensional object is a transformation of the shape object into a one dimensional line introducing skeleton shape descriptors. Many operations like shape representation and deformation can be performed more efficiently on the skeleton than on the full object, as skeleton is simpler than the original object. The parameters such as thresholds, bounds and weights have to be tuned for the successful performance of the object recognition system. This paper provides an overview of estimating the parameters for performance evaluation of the object detection techniques, and a survey of Performance evaluation of junction detection schemes in digital image processing.
Keywords: Performance analysis, Roc analysis, Performance Criteria, Parameter selection, Junction detection
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