Learning OpenCV

Chapter 8. Contours

Although algorithms like the Canny edge detector can be used to find the edge pixels that separate different segments in an image, they do not tell you anything about those edges as entities in themselves. The next step is to be able to assemble those edge pixels into contours. By now you have probably come to expect that there is a convenient function in OpenCV that will do exactly this for you, and indeed there is: cvFindContours(). We will start out this chapter with some basics that we will need in order to use this function. Specifically, we will introduce memory storages, which are how OpenCV functions gain access to memory when they need to construct new objects dynamically; then we will learn some basics about sequences, which are the objects used to represent contours generally. With those concepts in hand, we will get into contour finding in some detail. Thereafter we will move on to the many things we can do with contours after they've been computed.

Memory Storage

OpenCV uses an entity called a memory storage as its method of handling memory allocation for dynamic objects. Memory storages are linked lists of memory blocks that allow for fast allocation and de-allocation of continuous sets of blocks. OpenCV functions that require the ability to allocate memory as part of their normal functionality will require access to a memory storage from which to get the memory they require (typically this includes any function whose output is of variable size). ...