Image Thresholding Technique Based On Fuzzy Partition And Entropy Maximization

Thresholding is a commonly used technique in image segmentation because of its fast and easy application. For this reason threshold selection is an important issue. There are two general approaches to threshold selection. One approach is based on the histogram of the image while the other is based on the gray scale information located in the local small areas. The histogram of an image contains some statistical data of the grayscale or color ingredients. In this thesis, an adaptive logical thresholding method is proposed for the binarization of blueprint images first. The new method exploits the geometric features of blueprint images. This is implemented by utilizing a robust windows operation, which is based on the assumption that the objects have "e;C"e; shape in a small area. We make use of multiple window sizes in the windows operation. This not only reduces computation time but also separates effectively thin lines from wide lines. Our method can automatically determine the threshold of images. Experiments show that our method is effective for blueprint images and achieves good results over a wide range of images. Second, the fuzzy set theory, along with probability partition and maximum entropy theory, is explored to compute the threshold based on the histogram of the image. Fuzzy set theory has been widely used in many fields where the ambiguous phenomena exist since it was proposed by Zadeh in 1965. And many thresholding methods have also been developed by using this theory. The concept we are using here is called fuzzy partition. Fuzzy partition means that a histogram is parted into several groups by some fuzzy sets which represent the fuzzy membership of each group because our method is based on histogram of the image . Probability partition is associated with fuzzy partition. The probability distribution of each group is derived from the fuzzy partition. Entropy which originates from thermodynamic theory is introduced into communications theory as a commonly used criteria to measure the information transmitted through a channel. It is adopted by image processing as a measurement of the information contained in the processed images. Thus it is applied in our method as a criterion for selecting the optimal fuzzy sets which partition the histogram. To find the threshold, the histogram of the image is partitioned by fuzzy sets which satisfy a certain entropy restriction. The search for the best possible fuzzy sets becomes an important issue. There is no efficient method for the searching procedure. Therefore, expansion to multiple level thresholding with fuzzy partition becomes extremely time consuming or even impossible. In this thesis, the relationship between a probability partition (PP) and a fuzzy C-partition (FP) is studied. This relationship and the entropy approach are used to derive a thresholding technique to select the optimal fuzzy C-partition. The measure of the selection quality is the entropy function defined by the PP and FP. A necessary condition of the entropy function arriving at a maximum is derived. Based on this condition, an efficient search procedure for two-level thresholding is derived, which makes the search so efficient that extension to multilevel thresholding becomes possible. A novel fuzzy membership function is proposed in three-level thresholding which produces a better result because a new relationship among the fuzzy membership functions is presented. This new relationship gives more flexibility in the search for the optimal fuzzy sets, although it also increases the complication in the search for the fuzzy sets in multi-level thresholding. This complication is solved by a new method called the "e;Onion-Peeling"e; method. Because the relationship between the fuzzy membership functions is so complicated it is impossible to obtain the membership functions all at once. The search procedure is decomposed into several layers of three-level partitions except for the last layer which may be a two-level one. So the big problem is simplified to three-level partitions such that we can obtain the two outmost membership functions without worrying too much about the complicated intersections among the membership functions. The method is further revised for images with a dominant area of background or an object which affects the appearance of the histogram of the image. The histogram is the basis of our method as well as of many other methods. A "e;bad"e; shape of the histogram will result in a bad thresholded image. A quadtree scheme is adopted to decompose the image into homogeneous areas and heterogeneous areas. And a multi-resolution thresholding method based on quadtree and fuzzy partition is then devised to deal with these images. Extension of fuzzy partition methods to color images is also examined. An adaptive thresholding method for color images based on fuzzy partition is proposed which can determine the number of thresholding levels automatically. This thesis concludes that the "e;C"e; shape assumption and varying sizes of windows for windows operation contribute to a better segmentation of the blueprint images. The efficient search procedure for the optimal fuzzy sets in the fuzzy-2 partition of the histogram of the image accelerates the process so much that it enables the extension of it to multilevel thresholding. In three-level fuzzy partition the new relationship presentation among the three fuzzy membership functions makes more sense than the conventional assumption and, as a result, performs better. A novel method, the "e;Onion-Peeling"e; method, is devised for dealing with the complexity at the intersection among the multiple membership functions in the multilevel fuzzy partition. It decomposes the multilevel partition into the fuzzy-3 partitions and the fuzzy-2 partitions by transposing the partition space in the histogram. Thus it is efficient in multilevel thresholding. A multi-resolution method which applies the quadtree scheme to distinguish the heterogeneous areas from the homogeneous areas is designed for the images with large homogeneous areas which usually distorts the histogram of the image. The new histogram based on only the heterogeneous area is adopted for partition and outperforms the old one. While validity checks filter out the fragmented points which are only a small portion of the whole image. Thus it gives good thresholded images for human face images

Spectral analysis and resolving spatial ambiguities in human sound localization

This dissertation provides an overview of my research over the last five years into the spectral analysis involved in human sound localization. The work involved conducting psychophysical tests of human auditory localization performance and then applying analytical techniques to analyze and explain the data. It is a fundamental thesis of this work that human auditory localization response directions are primarily driven by the auditory localization cues associated with the acoustic filtering properties of the external auditory periphery, i.e., the head, torso, shoulder, neck, and external ears. This work can be considered as composed of three parts. In the first part of this work, I compared the auditory localization performance of a human subject and a time-delay neural network model under three sound conditions: broadband, high-pass, and low-pass. A “black-box” modeling paradigm was applied. The modeling results indicated that training the network to localize sounds of varying center-frequency and bandwidth could degrade localization performance results in a manner demonstrating some similarity to human auditory localization performance. As the data collected during the network modeling showed that humans demonstrate striking localization errors when tested using bandlimited sound stimuli, the second part of this work focused on human sound localization of bandpass filtered noise stimuli. Localization data was collected from 5 subjects and for 7 sound conditions: 300 Hz to 5 kHz, 300 Hz to 7 kHz, 300 Hz to 10 kHz, 300 Hz to 14 kHz, 3 to 8 kHz, 4 to 9 kHz, and 7 to 14 kHz. The localization results were analyzed using the method of cue similarity indices developed by Middlebrooks (1992). The data indicated that the energy level in relatively wide frequency bands could be driving the localization response directions, just as in Butler’s covert peak area model (see Butler and Musicant, 1993). The question was then raised as to whether the energy levels in the various frequency bands, as described above, are most likely analyzed by the human auditory localization system on a monaural or an interaural basis. In the third part of this work, an experiment was conducted using virtual auditory space sound stimuli in which the monaural spectral cues for auditory localization were disrupted, but the interaural spectral difference cue was preserved. The results from this work showed that the human auditory localization system relies primarily on a monaural analysis of spectral shape information for its discrimination of directions on the cone of confusion. The work described in the three parts lead to the suggestion that a spectral contrast model based on overlapping frequency bands of varying bandwidth and perhaps multiple frequency scales can provide a reasonable algorithm for explaining much of the current psychophysical and neurophysiological data related to human auditory localization

Quenching of FITC fluorescent lyophilisomes by trypan blue in the absence of cells.

<p>Results show decreased fluorescence (a) and efficient quenching (b) up to three washings steps of FITC fluorescent lyophilisomes by trypan blue.</p

Sorting of lyophilisomes by fluorescence-activated cell sorting.

<p>a/b) A representative size distribution of the initial lyophilisome population (a) and sorted lyophilisomes (b) is depicted, showing smaller lyophilisomes after sorting. Note the difference in x and y axes. c) Initial lyophilisome population depicted in a FACS dot plot with forward (size)/FITC-positive lyophilisome (FL1 channel) scatter where gated FITC-positive lyophilisomes were sorted. d) After sorting, the scatter showed merely small lyophilisomes, as large lyophilisomes were removed.</p

Cellular binding and internalization of unmodified lyophilisomes and TAT-conjugated lyophilisomes.

<p>HeLa, OVCAR-3, Caco-2 and SKOV-3 cells incubated with TAT-conjugated and unmodified lyophilisomes resulted in 86±3% and 12±4%, 87±3% and 16±8%, 97±3% and 19±3%, and 95±10% and 67±20% lyophilisome-positive cells, respectively. TAT  =  trans-activating transcriptional activator. *p<0.01 ***p<0.0001.</p

Cellular uptake of TAT-conjugated lyophilisomes as analyzed by transmission electron microscopy.

<p>HeLa cells were incubated with unmodified (a) and TAT-conjugated lyophilisomes (b-d) for 4 h. a) No attachment or uptake was observed using unmodified lyophilisomes. b-d) TAT-conjugated lyophilisomes (white arrows) showed various processes required for effective drug delivery systems, such as attachment (b) and uptake (c). Additionally, signs of degradation of the capsule inside the cell were visualized (black arrows, d). Scale bar represents 1.0 µm. TAT  =  trans-activating transcriptional activator.</p

Schematic illustration of the conjugation of the cell-penetrating peptide (CPP) TAT to lyophilisomes.

<p>(1) Primary amine groups of lyophilisomes react with Sulfo-GMBS introducing reactive maleimide groups. (2) CPPs (cysteine-functionalized TAT-peptides; C-Ahx-YGRKKRRQRRR) are conjugated to maleimide-conjugated lyophilisomes, resulting in stable CPP-conjugated lyophilisomes. Sulfo-GMBS  =  sulfo-<i>N</i>-[γ-maleimidobutyryloxy]sulfo succinimide ester; Ahx  =  aminohexanoic acid; TAT  =  trans-activating transcriptional activator.</p

Internalization of lyophilisomes with and without TAT peptide into HeLa cells.

<p>FACS showed a large number of lyophilisome-positive cells for TAT-conjugated lyophilisomes after 1 h (67±3%) without trypan blue and a cellular uptake of 25±1% with trypan blue. Values for lyophilisomes without TAT peptide were low. When lyophilisomes were incubated for 4 h, TAT-conjugated lyophilisomes conserved the large number of lyophilisome-positive cells (79±8%) with an increased internalization of 59±14%, while unmodified lyophilisomes still showed few lyophilisome-positive cells and little cellular uptake. *p<0.01 **p<0.001. CPP  =  cell penetrating peptide; TAT  =  trans-activating transcriptional activator.</p

Comparison of European ICU patients in 2012 (ICON) versus 2002 (SOAP)

Purpose: To evaluate differences in the characteristics and outcomes of intensive care unit (ICU) patients over time. Methods: We reviewed all epidemiological data, including comorbidities, types and severity of organ failure, interventions, lengths of stay and outcome, for patients from the Sepsis Occurrence in Acutely ill Patients (SOAP) study, an observational study conducted in European intensive care units in 2002, and the Intensive Care Over Nations (ICON) audit, a survey of intensive care unit patients conducted in 2012. Results: We compared the 3147 patients from the SOAP study with the 4852 patients from the ICON audit admitted to intensive care units in the same countries as those in the SOAP study. The ICON patients were older (62.5 ± 17.0 vs. 60.6 ± 17.4 years) and had higher severity scores than the SOAP patients. The proportion of patients with sepsis at any time during the intensive care unit stay was slightly higher in the ICON study (31.9 vs. 29.6%, p = 0.03). In multilevel analysis, the adjusted odds of ICU mortality were significantly lower for ICON patients than for SOAP patients, particularly in patients with sepsis [OR 0.45 (0.35–0.59), p < 0.001]. Conclusions: Over the 10-year period between 2002 and 2012, the proportion of patients with sepsis admitted to European ICUs remained relatively stable, but the severity of disease increased. In multilevel analysis, the odds of ICU mortality were lower in our 2012 cohort compared to our 2002 cohort, particularly in patients with sepsis. © 2018, The Author(s)