Sentence examples for effective texture from inspiring English sources
We present a novel approach to multi-texture image segmentation based on the formation of an effective texture feature vector.
Ojala et al. have introduced the local binary patterns (LBP) for effective texture description that has been used in many image processing and computer vision applications [15].
However, effective texture patterns and dimensions on a tool surface are still difficult to obtain and suitable textures can be obtained only by trial and error.
The conventional approach typically extracts microstructures (edges, corners, spots, etc). of the images, while the hierarchy allows for the extraction of both micro- and macro-structures [22], which are required for effective texture extraction and discrimination.
For quality determination based on these image datasets, effective texture classification methodology is essential to handle highly dimensional images and to extract quality-related information from these product surface images.
Next the texture features are integrated with a local binary pattern, to form an effective texture descriptor with low computational cost, which overcomes the weakness of the single frequency output component of the filter.
For the visual design of 3D scenes, in particular, effective texturing depends significantly on how important contents are expressed, e.g., by preserving global salient structures, and how their depiction is cognitively processed by the user in an application context.
Experimental works confirm that they are effective for texture retrieval.
This paper presents a simple and effective missing texture reconstruction method based on a perceptually optimized algorithm.
In this paper, we present a simple and effective missing texture reconstruction method based on a perceptually optimized algorithm.
