This thesis examines and presents contributions to the intra-frame texture coding of Object-Based Image Coding. Two coding approaches are focused: the block-based DCT and the shape-adaptive DCT (SA-DCT). Morphological features are proposed in order to extract intrinsic characteristics of shape and texture from the object to be encoded. These features classify the 8 X 8 image blocks according to their number of object pixels. These morphological features are used both in the analysis of coding algorithms reported in the literature and in the design of hybrid schemes that overcome some problems identified during the analysis procedure. The proposed hybrid schemes employ different strategies to deal with different groups of blocks. The information about the mean texture value at these groups is used as the basis of the algorithms. Finally, an adaptive coding structure, which is a function of the bit rate, texture and shape of the object, is proposed. This strategy incorporates the hybrid schemes introduced in this thesis, in order to choose the preferential processing direction for the EI - Extension Interpolation - padding technique and for the SA-DCT. It automatically selects the more adequate approach for a specific group of blocks at a given bit rate, depending on the morphological features. Performance of this adaptive coding scheme is either comparable or better than the best object-based transform coding schemes reported in the literature. This is valid both at low and high bit rates. Results are presented in terms of PSNR performance curves and subjective quality of the decoded images.