Thinning is the important technique used in the image processing. The first step in the Thinning is “PreProcessing”. This Thinning technique is used to represent the structural shape of the image. This thinning technique is used to compress the image and also to display the skeleton of the image. Skeletonization is a process of reducing foreground regions of a binary image to a skeleton form th...

-Binary image representation by its morphological skeleton transform has been proposed in the past as an information preserving representation. In this paper this skeleton representation is adopted as the start point for the development of a binary shape recognition scheme. A skeleton matching algorithm is presented that efficiently characterizes the similarity between two skeletons as a distan...

Shape description is an important step in image analysis. Skeletonization methods are widely used in image analysis as they are a powerful tool to describe a shape. Indeed, a skeleton is a one point wide line centered in the shape which keeps the shape’s topology. Commonly, at least two scans of the image are needed for the skeleton computation in the state of art methods of skeletonization. In...

The skeleton is a continuous planar shape for representation as a kind of primitive of the original. The skeleton efficiently concentrates the topological information of the original shape. It is particularly useful for representing amorphous, irregular shapes that cannot be treated by more conventional geometrical methods. The possible applications include the creation of shape primitives, cur...

The skeleton of an image object is a simplified representation, which is of great significance for the image recognition and matching. To obtain a smooth and accurate skeleton of a specified object in the gray image, this paper provides a unified framework by combining the level set idea with the gradient module method. The intrinsic procedure involves three steps. First, an energy function is ...

An evaluative methodology and five accompanying performance measures were developed to quantitatively assess the performance of the skeleton projection algorithm constituting the heart of tract-based spatial statistics (TBSS). The performance measures were designed to quantify the accuracy of skeleton projection in its indented task of alleviating any residual misalignment that may remain after...

Four algorithmic skeletons for low-level image processing and intermediate-level computer vision are presented, related to a common divide and conquer higher order function. The parallel operation of each skeleton is described and their use in a complete parallel multisource image segmentation system is discussed.

This paper presents the recognition of shapes for object retrieval in image databases using skeleton-based and contour-based representation by discrete curve evaluation and two consecutive primitive edges. Humans tend to use high-level concepts in everyday life. Object segmentation and recognition is the primary step of computer vision to achieve image retrieval of high-level image analysis. Co...