Best Clustering Around the Color Images

Hosseini, Seyyed Meysam; Farsi, Hasan; Yazdi, Hadi Sadoghi

doi:10.7763/ijcee.2009.v1.4

Cited by 6 publications

(4 citation statements)

References 13 publications

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“…See also [55] for a similar conversion-based method through a 3 × 3 matrix, where we used quadratic programming and GA to produce a new color space for lip detection. Based on our previous experiments in [55] we realized that color feature could be a powerful tool to train supervised classification methods. Two methods are proposed in this paper to obtain the mentioned conversion matrix; linear and quadratic transformations.…”

Section: The Proposed Approachmentioning

confidence: 99%

A target-based color space for sea target detection

2011

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Sea target detection is a vital application for military and navigation purposes. A new supervised clustering method based on the combination of the PSO and FCM techniques is presented for the sea target detection problem. The color components of the target and non-target pixels in the RGB color space are used as features to train the classification algorithm. The new classifier is presented in the form of a new color space which we call the Target-based Color Space (TCS); in fact the RGB color space is converted to this new space through a 3 × 3 matrix. The Particle Swarm Optimization (PSO) algorithm is then used to search for the optimum weights of the conversion matrix which results in a more discriminating clustering space between the target and non-target pixels. In other words, solving the optimization problem, minimization of the objective function of the FCM clustering technique in linear and quadratic transform domain (with a NP-hard problem in quadratic conversion), is done using the PSO algorithm. The main objective of this work is to demonstrate the efficiency of using just color features, as well as color space conversion in the classification domain. Experimental results show the efficiency of new method in finding sea targets in color images.

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Section: The Proposed Approachmentioning

confidence: 99%

A target-based color space for sea target detection

2011

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“…Many factors prevent accurate segmentation by using these methods, such as complex backgrounds, lighting changes, and poor image quality. To solve these problems, researchers have turned to neural networks [14]. Neural network-based methods have been known to be robust in identifying data patterns, which are superior in speed, flexible against environmental changes, and provide higher performance compared to classic statistical models.…”

Section: Related Workmentioning

confidence: 99%

Estimation of Hand Skeletal Postures by Using Deep Convolutional Neural Networks

Gheitasi

Farsi

Mohamadzadeh

2020

IJE

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Hand posture estimation attracts researchers because of its many applications. Hand posture recognition systems simulate the hand postures by using mathematical algorithms. Convolutional neural networks have provided the best results in the hand posture recognition so far. In this paper, we propose a new method to estimate the hand skeletal posture by using deep convolutional neural networks. To simplify the proposed method and to be more functional, the depth factor is ignored. So only the simple color images of hands are used as inputs of the system. The proposed method is evaluated by using two datasets with high-diversity named Mixamo and RWTH, which include 43,986 and 1160 color images, respectively, where 74% of these images are selected as a training set and, 26% of the rest images are selected as the evaluation set. The experiments show that the proposed method provides better results in both hand posture recognition and detection of sign languages compared to state-of-the-art methods.

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“…Semicarbazones are a Schiff base compound bearing N, O-chelating site for complexation 12 . They can bind transition and non-transition ions and have a range of exciting applications, including their pharmaceutical and biological acti-vities 12,13 . Semicarbazone Schiff base compounds have a range of applications, including their ability to bind with DNA and act as antibacterial, antifungal, anticancer, antiinflammatory, antioxidant, antiviral, analgesic, and anticonvulsant agents [14][15][16] .…”

Section: Introductionmentioning

confidence: 99%

New dimeric complexes with semicarbazone mannich-based ligand; formation, structural investigation and biological activity

Abaas,

Al-Jeboori

2023

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The formation of a new semicarbazone Schiff-base ligand (E)-2-(2-(phenyl(2-phenylhydrazinyl)- methyl)cyclohexylidene)hydrazine-1-carboxamide (HL) and its complexes are reported. The new ligand was prepared from the condensation of the Mannich-base 2-(phenyl(2-phenylhydrazinyl)methyl)cyclohexan-1-one (M) with the semicarbazide. A series of metal complexes were prepared by the reaction of the ligand with the metal chlorides of Cr(III), Mn(II), Co(II), Ni(II), Cu(II)), Zn(II) and Cd(II). The structure of the ligand and its complexes were elucidated through analytical and spectroscopic techniques. The analyses indicated the ligand behaves as a monobasic tridentate species and the isolation of dimeric complexes with the general formula; [Cr(L)(Cl)2(H2O)]2, [M(L)Cl]2 (where M= Mn(II), Co(II), Ni(II), Cu(II)), Zn(II) and Cd(II)). These studies revealed a distorted octahedral geometry for Cr(III), a distorted square planar for Cu(II) and a tetrahedral arrangement for Mn(II), Co(II), Ni(II), Zn(II) and Cd(II). The biological activity of the prepared compounds against Escherichia coli, Pseudomonas auroginosa, Staphylococcus aureus and Bacillus subtilis compared with Cefotaxime (as a standard antibiotic) was also explored. Some of the examined compounds indicated a similar antibacterial activity to Cefotaxime. Furthermore, antifungal activity against Candida albicans and Rhizopus sporium was investigated, which showed that the ligand and its complexes exhibited good antifungal activity. Keywords: Schiff-base ligand; Structural characterization; Dimeric semicarbazone complexes; Biological activity.

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Best Clustering Around the Color Images

Cited by 6 publications

References 13 publications

A target-based color space for sea target detection

A target-based color space for sea target detection

Estimation of Hand Skeletal Postures by Using Deep Convolutional Neural Networks

New dimeric complexes with semicarbazone mannich-based ligand; formation, structural investigation and biological activity

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