Multi-focus image fusion is an effective technique to extend the depth-of-field of optical
lenses by creating an all-in-focus image from a set of partially focused images of the same …

Image classification is a complex process that may be affected by many factors. This paper
examines current practices, problems, and prospects of image classification. The emphasis …

Deep convolutional neural networks (DCNNs) have led to breakthrough results in numerous
practical machine learning tasks, such as classification of images in the ImageNet data set …

A number of industries use human inspection to visually classify the quality of their products
and the raw materials used in the production process, this process could be done …

This paper describes the sequence of construction of a cell nuclei classification model by the
analysis, the characterization and the classification of shape and texture. We describe first …

We have witnessed great interest and a wealth of promise in content-based image retrieval
as an emerging technology. While the last decade laid foundation to such promise, it also …

Hyperspectral images provide higher spectral resolution than typical RGB images by
including per-pixel irradiance measurements in a number of narrow bands of wavelength in …

Fruit classification is a difficult challenge due to the numerous types of fruits. In order to
recognize fruits more accurately, we proposed a hybrid classification method based on …

We present here SIMPLIcity (semantics-sensitive integrated matching for picture libraries),
an image retrieval system, which uses semantics classification methods, a wavelet-based …

Local or global rotation invariant feature extraction has been widely used in texture
classification. Local invariant features, eg local binary pattern (LBP), have the drawback of …