Soft-biometrics play an important role in face biometrics and related fields since these might lead to biased performances, threaten the user's privacy, or are valuable for commercial aspects. Current databases specifically constructed development of recognition applications. Consequently, contain a large number images but lack attribute annotations overall annotation correctness. In this work,...

Major challenges in camera-base document analysis are dealing with uneven shadows, high degree of curl and perspective distortions. In CBDAR 2007, we introduced the first dataset (DFKI-I) of camera-captured document images in conjunction with a page dewarping contest. One of the main limitations of this dataset is that it contains images only from technical books with simple layouts and moderat...

finger vein is one of the most fitting biometric for identifying individuals. in this paper a new method for finger vein recognition is proposed. first the veins are extracted from finger vein images by using entropy based thresholding. in finger vein images the veins are appeared as dark lines. the method extracts veins as well, but the images are noisy, that means in addition to the veins the...

This paper presents a large gathering dataset of images extracted from publicly filmed videos by 24 cameras installed on the premises Masjid Al-Nabvi, Madinah, Saudi Arabia. consists raw and processed reflecting highly challenging unconstraint environment. The methodology for building four core phases; that include acquisition videos, extraction frames, localization face regions, cropping resiz...

The lack of a standard muzzle print database is a challenge for conducting researches in Arabian horse identification systems. Therefore, collecting a muzzle print images database is a crucial decision. The dataset presented in this paper is an option for the studies that need a dataset for testing and comparing the algorithms under development for Arabian horse identification. Our collected da...

Medical datasets are often highly imbalanced with overrepresentation of common medical problems and a paucity of data from rare conditions. We propose simulation of pathology in images to overcome the above limitations. Using chest X-rays as a model medical image, we implement a generative adversarial network (GAN) to create artificial images based upon a modest sized labeled dataset. We employ...