Image processing of grinding wheel surface

Identifying the situation of grinding wheel wear and loading is a very important issue for high efficiency grinding operations. This paper presents a new method that detects and identifies the chip loading and cutting edge wear of a grinding wheel using the image processing toolbox of MATLAB. The different optical characters of the metal chips and the abrasive grains are analysed. The Sobel operator is adopted to make edge detection. A sensitivity threshold based on the global condition is used to decrease the noise. Image dilation and erosion processes are used to ensure the edge of each loaded chip is covered by a continuous section. The ratios of chips are calculated and displayed to monitor the wheel surface working status

Semantics in Content-based Multimedia Retrieval

This contribution investigates the content-based feature extraction methods used in visual information retrieval, focusing on concepts that are employed for the semantic representation of media content. The background part describes the building blocks of feature extraction functions. Since numerous methods have been proposed we concentrate on the metaconcepts. The building blocks lead to a discussion of starting points for semantic enrichment of low-level features. The second part reviews features from the perspective of data quality. A case study on content-based MPEG-7 features illustrates the relativity of terms like “low-level, ” “highlevel” and “semantics”. For example, often more semantics mean just more redundancy. The final part sketches the application of features in retrieval scenarios. The results of a case study suggest that – from the retrieval perspective, too – “semantic enrichment of low-level features ” is a partially questionable concept. The performance of classification-based retrieval, it seems, does hardly depend on the context of features.