Binary Shape Coding Using 1-D Distance Values

Binary Shape Coding Using 1-D Distance Values from Baseline Shi Hwa Lee, Dae-Sung Cho, Yu-Shin Cho, Sehoon Son, Euee Jae-Seob Shin, and Yang Seok Seo

S.Jang,

Signal Processing Lab., Samsung Advanced Institute of Technology, P.O.Box 111, Suwon 440-600, Korea. E-mail: { shlee,dscho} @ dspsun. I sait .samsung.Co.kr ,

Abstract Here we describe a baseline-based binary shape coding method in which arbitrarily shaped object is represented b y the traced 1-D data from baseline and turning point (TP). The shape coding is performed based on contour-based method in each separated shape. There are two coding modes in shape coding, i.e. intra and inter mode as in texture coding. In inter coding mode, object identification, global shape matching, and local contour matching are used. I n intra mode and residue coding, the DPCM values of T P and the 1-D dzstance values of the shape are encoded b y fixed arithmetic encoder. Simulation results show that the proposed method has better codzng eficiency and subjective quality compared with the block-based method i.e. context arithmetic encoding (CAE).

1

Distancebehueen conlouisnmple SI and the baseline

Bllscline (horizontal)

= DfSIJ

:..... '

:TPs(TurningPoinrs): SlO.S1Z.S17

Figure 1: Contour trace

Introduction

Binary shape coding is one of the key issues in the standardization of MPEG-4 [l][2] which is considering audio-visual coding in multimedia applications allowing for content based interactivity and high compression. This shape coding is one of new features in MPEG-4 different with other standard such as MPEG1 and MPEG-2. In low bit-rate coding the bit rates for shape have large portion in the coder. To improve the coding efficiency the temporal correlation between consecutive two objects is also considered. In addition t o the coding efficiency, it is also important t o improve subjective quality of reconstructed shape in lossy coding since the distortion of shape is more sensitive t o human eyes than that of the texture. However current verification model (CAE) in MPEG4 is not good to subjective quality because of stair effects on reconstructed shape due to the block-based size conversions [ 3 ] . Thoe problem of stair effect can be solved by compressing boundary contour directly. The proposed shape coding method called baseline shape coding is a kind of contour-based

0-8186-8183-7/97 $10.000 1997 IEEE

method. The 1-D contour data extracted based on a baseline and turning points (TPs) are detected in intra coding. All the extracted data are encoded by fixed arithmetic coder [ 5 ] . The algorithm is also partly described in [3].

2

Turning Point and 1-D Data Extraction

Once a baseline is chosen by selecting the long axis of minimum boundary rectangle of shape, we need t o extract the distance values from the baseline t o actual contour points of the shape. As shown in Fig. 1, there may be more than two contour pixels on the same line from a point on the baseline. For example, between two contour pixels s8 and ,522 there exist four contour pixels on the same line from the baseline. For data extraction we trace contour pixels clockwise or counter clockwise from on contour point and find the closest distance between baseline and the contour pixel. Consequently, we can find all distance values between baseline and all contour points. These values are arranged according t o the tracing order. One pass

508

Original Contour Segment

7

......................

Figure 3: Searching the corresponding shape of e from the previous shape:a,b,c

Figure 2: Adjustment of Sampling Positions

inserted. SAD (Sum of Absolute Difference) is used for evaluating error during defining SR. For coding the sequence of the sampled distance values, a SR value is coded in first. If SR is only one distance value is coded for the CS, if SR is two samples are DPCM encoded, and if SR is 1, all samples are encoded.

of tracing will cover all the connected contour pixels. Still there is a chance that some contour pixels are missing when the pixels are not connected with the current contour pixels (e.g. holes). In Fig. 1, the trace starts from the contour point 5’1 and keep tracing Sf,53,..., 5’28. In the tracing process of the shape contour, we can get the distance between S; and the baseline, where D ( i ) (1 5 m 5 28) means the distance between 5’; and the baseline. Another information t o be coded is TPs, which means that the tracing changes the direction (forward t o backward or backward to forward). Slo,S12,and S17 in Fig. 1 are TPs. A decoder should know 1) the starting point of tracing, 2) 1D distance values D ( i ) (1 5 i 5 28), and 3) TPs, which