Sentence examples for low level image from inspiring English sources

The architecture's main component is an extensive library of data parallel low level image operations capable of running on homogeneous distributed memory MIMD-style multicomputers.

Without an additional source of knowledge, automatic image segmentation based on low level image features seemed unlikely to succeed in extracting semantic objects in generic images.

Instead of extracting rich information by expensive computation of image processing, we propose an inference mechanism from low level image features (e.g., optical flow), inspired by psychological research on how humans perceive motion.

Many existing methods have the problem that they are designed to exploit low level image descriptors (e.g. image pixels or image gradient) only, rather than high-level latent semantic concepts, thus there is no guarantee of human visual perception.

A number of low level image processing applications of the RFs such as impulse noise removal, speckle noise removal, adapting filtering, edge detection in noisy images, image sharpening and image frequency decomposition are outlined.

Another site, Ditto.com, is already using some low-level image analysis, in combination with keyword searching, to sort online images discovered by its Web crawlers.

The majority of them use low-level image searching, then incorporate keywords, speech-recognition systems and other data, like the time a photograph was taken, to refine the searches.

Then, low-level image pre-processing tasks are performed.

Figure 2 FPGA pipeline of low-level image processing.

Low-level image processing is an essential first step in any machine vision application.

These maps can encode high-level semantic features or low-level image features.