Taxonomic limits of Gonolobus (Apocynaceae: Asclepiadoideae) in the southeastern United States have been controversial, with some authors recognizing two species and others only one. Over the past 30 years, most authors have tended toward recognition of a single species. However, the morphological variation within the taxon appears complicated and has not been analyzed using a quantitative appr...

Images contain various types of useful information that should be extracted whenever required and this information may be in the form of text present in image. Extraction of this information involves detection, localization, extraction, enhancement and recognition of the text from the given image. Mathematical morphology is the foundation of morphological image processing, which consists of a s...

The abundant research on lexical access in the last 30 years has shown that context effects such as lexical status, morphological complexity, and neighborhood density can affect word recognition. Very little research has investigated interactions between perceptual distinctiveness and context effects. This study used a spoken word recognition in noise experiment with German words and nonwords t...

We present a novel way of generating unseen words, which is useful for certain applications such as automatic speech recognition or optical character recognition in low-resource languages. We test our vocabulary generator on seven low-resource languages by measuring the decrease in out-of-vocabulary word rate on a held-out test set. The languages we study have very different morphological prope...

This work proposes the use of machine learning methods applied to the construction of a gray level adaptive hitor-miss morphological operator. Because they are adaptive and translation invariant, it is expected that these operators can be better utilized for the process of pattern recognition. In a first approach, the investigated adaptive model is inspired on the Vector Quantization Unsupervis...

In this study, four statistical classifiers, namely linear discriminant classifier, quadratic discriminant classifier, k-Nearest Neighborhood classifier, and parzen classifier are considered for recognition of 2D-shapes. The octagonal shape features are identified from 2D-shapes with the morphological shape decomposition technique. These features are reduced using principle component analysis. ...