Images captured under poor illumination conditions often exhibit characteristics such as low
brightness, low contrast, a narrow gray range, and color distortion, as well as considerable …

The concept of intelligent visual identification of abnormal human activity has raised the
standards of surveillance systems, situation cognizance, homeland safety and smart …

Abstract In Magnetic Resonance Imaging (MRI), the poor quality images may not provide the
sufficient information for the visual interpretation of the affected locations of human body. So …

In the agriculture sector, soil classification plays a significant task, as it helps in soil tillage,
crop selection, moisture level estimation, and automation. Conventionally, soil classification …

Early identification of melanocytic skin lesions increases the survival rate for skin cancer
patients. Automated melanocytic skin lesion extraction from dermoscopic images using the …

Fruit classification is found to be one of the rising fields in computer and machine vision.
Many deep learning-based procedures worked out so far to classify images may have some …

Cracks are a common disease in road transportation infrastructure, while crack detection
has been a difficult task for a long time, especially for tunnels. Both training data and network …

Abstract Machine and deep learning applications play a dominant role in the current
scenario in the agriculture sector. To date, the classification of fruits using image features …

Image analysis technology has drawn dramatic attention and developed rapidly because it
enables a non-extractive and non-destructive approach to data acquisition of crab …

This paper presents contrast enhancement algorithms based on fuzzy contextual information
of the images. We introduce fuzzy similarity index and fuzzy contrast factor to capture the …