Query: Color image morphological processing

title: Morphological color image filter based on fuzzy combination and soft multi structural elements
abstract: A new filter on color morphology based on fuzzy combination and soft multi structural elements was presented.Color image pixels were sorted by the value of fuzzy combination.Morphological filter based on the ranking of fuzzy combination can get better results than based on the ranking of HSV.Experimental results demonstrate that the ability of color processing based on the new morphology is superior to the classical one,and that the algorithm possesses excellent performance on the noise restrained.

title: Fuzzy Mode Enhancement and Detection for Color Image Segmentation
abstract: This work lies within the scope of color image segmentation by pixel classification. The classes of pixels are constructed by detecting the modes of the spatial color compactness function, which characterizes the image by taking into account both the distribution of colors in the color space and their spatial location in the image plane. A fuzzy transformation of this function is performed, based on fuzzy morphological operators specifically designed for mode detection. Experimental segmentation results, using several synthetic and benchmark images, show the interest of the proposed method.

title: A Method for Color Image Edge Detection Based on Mathematical Morphology
abstract: Edge detection is a difficult problem in the processing of colored image,In this paper,a new colored edge detection algorithm based on mathematical morphology is proposed.The thought is: after being operated by certain structural element,the image is subtracted with the original one.The key of the algorithm is using morphological operator to corrode and inflate the image.The experimental result indicated that,the edge of the colored image can be well detected by using the algorithm,and the algorithm is superior to the Sobel and the Prewitt operator expanding methods in the protection to the tone,it can also examine the edge information of characteristic and background slowly transforming of image.

title: Image processing techniques for lemons and tomatoes classification
abstract: Vegetable quality is frequently referred to size, shape, mass, firmness, color and bruises from which fruits can be classified and sorted. However, technological by small and middle producers implementation to assess this quality is unfeasible, due to high costs of software, equipment as well as operational costs. Based on these considerations, the proposal of this research is to evaluate a new open software that enables the classification system by recognizing fruit shape, volume, color and possibly bruises at a unique glance. The software named ImageJ, compatible with Windows, Linux and MAC/OS, is quite popular in medical research and practices, and offers algorithms to obtain the above mentioned parameters. The software allows calculation of volume, area, averages, border detection, image improvement and morphological operations in a variety of image archive formats as well as extensions by means of "plugins" written in Java.

title: Application of rough sets to image pre processing for Face detection
abstract: Both of face detection and Face recognition play important role in the technology of biologic character identify. During processing of face image, it is indispensable to pre processing. In this paper, a Pre processing method for face color image based on rough sets theory is put forward. In this method, the image is divided as foreground and background by condition attribution. In order to extract the skin color regions, foreground is segmented by two kinds of the skin color model, YCrCb and HSV color spaces. Then, the opening and closing morphological operation are used to remove the small regions. Experiment shows the new algorithm has been tested by the computer simulation, in terms of accuracy extracting the skin color, positive rate of face detection and error rate etc. The results show that it can improve accuracy of extracting the skin color and shorten operation time validly. The result of enhanced image is better and satisfies requirement of face detection.

title: A volume image foreground identification method by dual multi scale morphological operations
abstract: A simple and regular foreground identification (FGID) method is proposed for image indexing. The gray level morphological open/close by reconstruction (MOR/MCR) is operated on one image in a dual and multi scale approach to construct a background gray level mesh to distinguish foregrounds (FGs) The highly regular MOR/MCR operations make it feasible to deal with FG segmentation of volume images. The FGID efficiency is verified by the image retrieval performance, i.e. recall, precision and rank.With precisely identified FGs, MPEG 7 shape descriptors, in additional to color ones, can be used to improve the image retrieval performance. For the retrieval unit, a greedy boosting retrieval method is used to perform shape based multiinstance query in considering the feature element dependency. To perform multi instance query with multiple features, the retrieval unit integrates the similarity ranks of different feature types according to the feature saliency among query samples to yield the final similarity rank. The normalized correlation coefficient of features among query samples is computed to provide weighting factors for integrating ranks. Experiments show that the FGID unit helps much in improving the retrieval performances, i.e. 7% improvement for the precision recall (PR) and 20% improvement for the averaged normalized modified retrieval rank (ANMRR) as compared to non FGID ones.

title: Automatic Identification of Tobacco Whiteflies Aphids and Thrips in Greenhouse Using Image Processing Techniques
abstract: Image processing algorithms for automatic identification of tobacco whiteflies, aphids and thrips which were stuck to a sticky trap placed in a greenhouse were proposed, implemented and tested in this study. Features of each insect were analyzed and evaluated and finally the size and color components of object were selected as the features for automatic identification. Aphid was easy to discriminate because it has small variation in color information and the size is different from other two kinds of insects. It was identified by extraction of its body part only and its ale parts were discarded because they did not have common morphological shapes when aphid stuck to a sticky trap and their color components also had huge variations. Thrips and TWs were identified after aphids were identified to reduce identification error. The reference values of size and color components are predetermined before the identification of target insects through experiments which was taken 50 insects each.  Automatic Identification, Tobacco Whiteflies, Aphids, Thrips, Image Processing Techniques

title: Comparison of Methods Measuring Pigmentation in Aquatic Animals and a New Application of Digital Image Acquisition and Processing
abstract: Body color is an important criterion of quality and price of aquatic animals. Several methods have been used to assess the pigmentation in the skin and flesh of these animals, depending on users' specific requirements such as practicality, applicability, accuracy, resource availability, etc. The methods for measuring pigmentation in aquatic animals can be grouped into chemical and physical ones, based on whether the chemical components or the physical color of the sample is measured. The methods were described and compared by the following criteria: method description, sample condition, instrumentation, time and costs and performance. The chemical methods are common methods used nowadays to analyze the pigmentation effect in aquatic animals, nevertheless, by combining the use of chemical and physical methods, correlation of pigment concentration and color can be achieved. A new application of digital image acquisition and processing allows the analysis of morphological and chromatic characteristics in chromatophores in aquatic animals at different developmental stages, opening new opportunities for further research in this field.

title: Automatic Tracing of Optic Disc and Exudates from Color Fundus Images Using Fixed and Variable Thresholds
abstract: The detection of bright objects such as optic disc (OD) and exudates in color fundus images is an important step in the diagnosis of eye diseases such as diabetic retinopathy and glaucoma. In this paper, a novel approach to automatically segment the OD and exudates is proposed. The proposed algorithm makes use of the green component of the image and preprocessing steps such as average filtering, contrast adjustment, and thresholding. The other processing techniques used are morphological opening, extended maxima operator, minima imposition, and watershed transformation. The proposed algorithm is evaluated using the test images of STARE and DRIVE databases with fixed and variable thresholds. The images drawn by human expert are taken as the reference images. The proposed method yields sensitivity values as high as 96.7% which are better than the results reported in the literature.

title: Multivariate mathematical morphology applied to colour image analysis
abstract: Mathematical morphology (MM) theory, founded by G. Matheron [MAT 75] and J. Serra [SER 82] is a powerful image analysis framework, currently fully developed for both binary and gray level images. Its popularity in the image processing community is mainly due to its rigorous mathematical foundation as well as its inherent ability to exploit the spatial relationships of pixels. The morphological framework provides a rich set of tools able to perform from the simplest to the most demanding tasks: noise reduction, edge detection, segmentation, texture and shape analysis, etc. As a methodology, it has been applied to almost all application areas dealing with digital image processing [SOI 03] Consequently, it was only a matter of time before attempting to extend the same concepts to color and more generally to multivalued images, i.e. images with more than one channel. This extension is not straightforward, however. Specifically, the morphological framework is based on complete lattices [HEI 94] In order to accommodate multi valued images, a way of calculating the extrema of vector data is essential. However, unlike scalars, there is no unambiguous way of ordering vectors. Even if most of the known vector ordering schemes have already been employed for defining multivariate morphological operators, none of them has yet been widely accepted.