A survey of different shape analysis techniques 1 A Survey of Different Shape Analysis Techniques -- Huang Nan

A survey of different shape analysis techniques 2 Abstract q Shape analysis methods play an important role in the computer vision applications. It is used for object recognition, matching, registration and analysis q This paper we will describe two major shape analysis categories, one is focus on the shape boundary (or contour) points and the other one is focus on the global (or interior) method.

A survey of different shape analysis techniques 3 Introduction 4 Retrieving images by their contents, instead of by other characters, is more and more becoming a operation strategy. 4 Two general methods for image comparison : *Intensity-based (color and texture) *Geometry-based(shape)

A survey of different shape analysis techniques 4 Introduction Common criteria need to be followed when develop or evaluate the shape description algorithms q Accessibility( cost of memory and running time) q Scope (how many kinds of shapes can be represent) q Uniqueness(result match to unique or multiple image)

A survey of different shape analysis techniques 5 Boundary Based Image Retrieval Algorithms Boundary scalar transform techniques Concept: Use one-dimensional function to represent the two- dimensional shape boundary. ---The result is scaleable but not a graph, an image or other values which like the shape.

A survey of different shape analysis techniques 6 Boundary Based Image Retrieval Algorithms Algorithms: ã Shape Centroid: Select acentroid point of the shape, the values of the 1-D function are the distances between shape centroid point and boundary points. The boundary points are selected based on the criteria that the central angles are equal. (Refer to the Figure 1) a0 a2 a1 a3 a4 0 Figure 1

A survey of different shape analysis techniques 7 Boundary Based Image Retrieval Algorithms Algorithms: ã Arc Height Function: An arc chord AB with a predefined length is insert on the boundary. A vertical line OC is cross the arc chord and separate AB to two same length parts. AB also reach the boundary at point OC. The length of OC is called the arc height at position A. As the arc chord is moved along the curve, a mapping between arc length and arc height defined the AHF. AB O arc C

A survey of different shape analysis techniques 8 Boundary Based Image Retrieval Algorithms Algorithms: ã Turing Function: Used a tangent angle versus arc length, the tangent angle at some point is measured relative to the tangent angle at the initial point. ã Line segmentation:Line segments are obtained by partitioning the radial line form the center of the mass to the boundary point. Segments are partitioned into parts within the shape and parts outside the shape.

A survey of different shape analysis techniques 9 Boundary Based Image Retrieval Algorithms Boundary Space Domain Techniques Concept: The Boundary space domain technique use shape boundary as input and produce the result as the format of graph or pictorial --- The result is a image, a graph, instead of scalar results

A survey of different shape analysis techniques 10 Boundary Based Image Retrieval Algorithms Algorithms: Chain Code: Developed by Freeman, an arbitrary boundary image is represented by a sequence of small vectors of unit length and limited set of possible directions

A survey of different shape analysis techniques 11 Boundary Based Image Retrieval Algorithms Algorithms: Chain Code:

A survey of different shape analysis techniques 12 Boundary Based Image Retrieval Algorithms Algorithms: Pairwise object recognition: ã Use the consecutive edgepoints to define the line segments which organizing the shape boundary. ã Let each line segment be a reference line on its turn., then comparing the reference line to all other lines and calculate the relative angle  between the reference line and each line, and the perpendicular minimum and maximum distance(d min and d max ) ã The histogram values are increased by one on the indexes corresponding to the angle  and the line segment from the d min to d max --- Used for the recognition of polygonal shapes

A survey of different shape analysis techniques 13 Boundary Based Image Retrieval Algorithms Algorithms: Pairwise object recognition: d max  Li L ref d min

A survey of different shape analysis techniques 14 Boundary Based Image Retrieval Algorithms Other Algorithms: ã Polygonal approximation: Use the polygonal line to approximately representing the boundary image. ã Boundary Decomposition: Estimate the orientational, scaling, and transnational data between the target image and model shape by using a small number of control points extracted from both shapes

A survey of different shape analysis techniques 15 Boundary Based Image Retrieval Algorithms Summary - The choice of the proper shape recognition method is always a compromise between recognition power and computational complexity 4 Chain Code: –Fast to calculate and it needs only a small amount of space –Can not preserve information on the exact shape of a boundary image 4 Pairwise histogram: –Computationally heavy and it requires more memory space 4 Polygonal approximation: –typically suitable for images which contain polygonal objects