The use of a shape is a popular way to define objects

and efficient shape coding is a key technique in object-based applications. Shape coding is also a hot research topic in the field of image and video signal processing

and many shape-coding techniques have been proposed. Among these methods

chain-coding is a popular technique that can be used for lossless shape coding. However

most existing chain-based shape-coding methods have not exploited the spatio-temporal redundancy contained within shape image sequences. Similar to the existence of strong spatio-temporal redundancy within and among video textures

a strong redundancy also exists within and between object contours. This redundancy can be exploited to improve coding efficiency. Hence

in this paper

a novel chain-based lossless shape-coding scheme is proposed by exploiting the spatio-temporal correlations among object contours to acquire high coding efficiency. First

for a given shape image sequence

the contours of visual objects are extracted

thinned to perfect single-pixel width

and transformed into chain-based representation frame by frame. Second

the activity of object contours in each frame is detected and evaluated. The shape frames are classified into two coding categories on the basis of this activity: intra-coding frames and inter-coding frames. If the contour activity in a frame is larger than a preset threshold

the activity will be encoded as an inter-coding frame; otherwise

it will be encoded as an intra-coding frame. For an intra-coding frame

the spatial correlations within object contours are exploited on the basis of chain-based spatial prediction and compensation. For an inter-coding frame

the temporal correlations among object contours are exploited on the basis of chain-based temporal prediction and compensation. Finally

a new method is introduced to efficiently encode the prediction residuals and motion displacements by analyzing the constraints among chain links. To evaluate the performance of the proposed scheme

experiments are conducted and a partial comparison is performed against some well-known existing methods

including the lossless coding scheme proposed by the Joint Bi-level Image Experts Group (JBIG)

the improved lossless coding scheme proposed by JBIG (JBIG2)

the Context-based Arithmetic Encoding with Intra-mode (CAE Intra) of MPEG-4

the Context-based Arithmetic Encoding with Inter-mode (CAE Inter) of MPEG-4

the Digital Straight Line Segments-based Coding with Intra-mode ( DSLSC Intra) and the Digital Straight Line Segments-based Coding with Inter-mode (DSLSC Inter)

are also presented.

The experimental results show that the average code length of our scheme is only 28.4% of JBIG

32.3% of JBIG2

39.9% of CAE Intra

78.1% of CAE Inter

48.4% of DSLSC Intra

and 94.0% of DSLSC Inter. As a whole

the proposed scheme outperforms all existing techniques and is considerably more efficient than other methods. As far as we know

the DSLSC Inter is the most efficient lossless shape-coding approach. However

compared with the DSLSC Inter

the proposed scheme has an average code length that can be reduced by 6%. The proposed scheme has wide prospects in many object-based images and video applications

such as object-based coding

object-based editing

and object-based retrieval.