Acknowledgment The authors acknowledge the support of the GAUK, grant No. 914813/2013, GA JU 134/2013/Z, project CENAKVA (CZ.1.05/2.1.00/01.0024) and grant GAČR No. 13-29225S. The authors would also like to thank the staff of Working place of tissue culture certified laboratory at Nové Hrady, namely Monika Homolková and Šárka Beranová for their assistance with the manual segmentation of the cel...

The competency to detect and to recognize the different denomination of coins is an essential expertise in the human beings life. This paper represents different algorithms for the detection and the recognition of coins which are highly overlapped. The proposed system includes three principal steps detection, extraction and recognition. This system is efficient in detecting and recognizing the ...

Seagrass ecosystems are coastal with high species diversity, especially fish. Fish diversity determines the abundance of communities based on number species. Detection fish directly (in-situ) and conventionally by catching them requires more energy, costs, relatively needs time. Therefore a computer vision method is needed that can detect well using underwater images. The detection model used M...

The cirrus clouds are a sort of transparent clouds that are barely visible in many satellite images. These clouds form a reflection effect in the images which hide the crucial information in remote sensing. Thus the removal of cirrus effect is essential to have an effective remote sensing over coastal regions and the following proposed algorithms proved to be cirrus-free images. The techniques ...

Segmentation partitions an image into its constituent parts. It is essentially the pre-processing stage of image analysis and computer vision. In this work, T1 and T2 weighted brain magnetic resonance images are segmented using multilevel thresholding and bacterial foraging optimization (BFO) algorithm. The thresholds are obtained by maximizing the between class variance (multilevel Otsu method...

In the literature, there are a lot of methods for image segmentation. Unfortunatelly, they are often limited in their capacity to treat image odtained by an acquisition system (Optical, X-Ray, IRM, . . .). Thus, many of them are dedicated to particular solutions and there is no generic method for solving the image segmentation problem. In this paper, we present a way to implement segmentation m...

Image processing is one of the real research regions in the most recent four decades. Numerous researchers have contributed very great algorithms and reported outstanding results. In this paper, state of matter search optimization based multilevel thresholding is implemented for the segmentation of gray scale Images. Set of standard gray level images are considered for image segmentation. The o...

Suspicious region segmentation is one of the most important parts CAD systems that are used for breast cancer detection in mammograms. In a system, there can be so many suspicious regions determined mammogram because complex structure breast. This study proposes hybrid thresholding method to use efficient mammograms and reducing number regions. The proposed provides fully-automatic based on det...

In this paper a novel edge detection method has been proposed which outperform Otsu method [1]. The proposed detection algorithm has been devised using the concept of genetic algorithm in spatial domain. The key of edge detection is the choice of threshold; which determines the results of edge detection. GA has been used to determine an optimal threshold over the image. Results are compared wit...

Abstract Traditional exhaustive search methods have high time complexity in solving multilevel threshold problems. To address this problem, a Levy flight based firefly algorithm called LFA is proposed. Otsu regard as its objective function. A series of standard test images were used to evaluate the performance algorithm. The Peak signal noise ratio(PSNR) and Structural similarity index (SSIM) a...