Image Retrieval Using Gradient Operators

The images are described by its content like color, texture, and shape information present in them.In this paper novel image retrieval methods discussed based on shape features extracted using gradient operators like Robert, Sobel, Prewitt and Canny. Masking of Gradient operators takes place for continuing the discontinue edges. Morphological operations like erosion and dilation are used along with canny. The proposed image retrieval techniques are tested on generic image database images spread across different categories. Gradient operators features are extracted using Figure of Merit (FOM). The average precision and recall of all queries are computed and considered for performance analysis. The performance ranking of the masks for proposed image retrieval methods can be listed as Robert, Canny, Prewitt, and Sobel

The Bulgeless Seyfert/LINER Galaxy NGC 3367: Disk, Bar, Lopsidedness and Environment

NGC3367 is a nearby isolated active galaxy that shows a radio jet, a strong bar and evidence of lopsidedness. We present a quantitative analysis of the stellar and gaseous structure of the galaxy disk and a search for evidence of recent interaction based on new UBVRI Halpha and JHK images and on archival Halpha Fabry-Perot and HI VLA data. From a coupled 1D/2D GALFIT bulge/bar/disk decomposition an (B/D ~ 0.07-0.1) exponential pseudobulge is inferred in all the observed bands. A NIR estimate of the bar strength = 0.44 places NGC 3367 bar among the strongest ones. The asymmetry properties were studied using (1) optical and NIR CAS indexes (2) the stellar (NIR) and gaseous (Halpha, HI) A_1 Fourier mode amplitudes and (3) the HI integrated profile and HI mean intensity distribution. While the average stellar component shows asymmetry values close to the average found in the Local Universe for isolated galaxies, the young stellar component and gas values are largely decoupled showing significantly larger A_1 mode amplitudes suggesting that the gas has been recently perturbed. Our search for (1) faint stellar structures in the outer regions (up to u_R ~ 26 mag arcsec^{-2}), (2) (Halpha) star-forming satellite galaxies and (3) regions with different colors (stellar populations) along the disk all failed. Such an absence is interpreted using recent numerical simulations to constrain a tidal event with an LMC like galaxy to some dynamical times in the past or to a current very low mass, gas rich accretion. We conclude that a cold accretion mode (gas and small/dark galaxies) may be responsible of the nuclear activity and peculiar (young stars and gas) morphology regardless of the highly isolated environment. Black hole growth in bulgeless galaxies may be triggered by cosmic smooth mass accretion.Comment: 27 pages, 12 figures, accepted for publication in The Astronomical Journa

The Acidic Tail of the Cdc34 Ubiquitin-conjugating Enzyme Functions in Both Binding to and Catalysis with Ubiquitin Ligase SCFC^(dc4*)

Ubiquitin ligases, together with their cognate ubiquitin-conjugating enzymes, are responsible for the ubiquitylation of proteins, a process that regulates a myriad of eukaryotic cellular functions. The first cullin-RING ligase discovered, yeast SCF^(Cdc4), functions with the conjugating enzyme Cdc34 to regulate the cell cycle. Cdc34 orthologs are notable for their highly acidic C-terminal extension. Here we confirm that the Cdc34 acidic C-terminal tail has a role in Cdc34 binding to SCF^(Cdc4) and makes a major contribution to the submicromolar K_m of Cdc34 for SCF^(Cdc4). Moreover, we demonstrate that a key functional property of the tail is its acidity. Our analysis also uncovers an unexpected new function for the acidic tail in promoting catalysis. We demonstrate that SCF is functional when Cdc34 is fused to the C terminus of Cul1 and that this fusion retains partial function even when the acidic tail has been deleted. The Cdc34-SCF fusion proteins that lack the acidic tail must interact in a fundamentally different manner than unfused SCF and wild type Cdc34, demonstrating that distinct mechanisms of E2 recruitment to E3, as is seen in nature, can sustain substrate ubiquitylation. Finally, a search of the yeast proteome uncovered scores of proteins containing highly acidic stretches of amino acids, hinting that electrostatic interactions may be a common mechanism for facilitating protein assembly

Variable size block truncation coding with adaptive bit plane omission for image compression

A modified version of the Block Truncation Coding (BTC), which is a non-information preserving image compression technique, is studied. The first modification is the introduction of variable block sizes to the standard BTC technique. The second modification is the adaptive omission of bit planes. Threshold selections for this modified BTC technique are analyzed in the context of the human visual system. Modified BTC techniques are compared against the standard technique from the point of view of visual image quality and compresion efficiency

Statistical modeling of RNA structure profiling experiments enables parsimonious reconstruction of structure landscapes.

RNA plays key regulatory roles in diverse cellular processes, where its functionality often derives from folding into and converting between structures. Many RNAs further rely on co-existence of alternative structures, which govern their response to cellular signals. However, characterizing heterogeneous landscapes is difficult, both experimentally and computationally. Recently, structure profiling experiments have emerged as powerful and affordable structure characterization methods, which improve computational structure prediction. To date, efforts have centered on predicting one optimal structure, with much less progress made on multiple-structure prediction. Here, we report a probabilistic modeling approach that predicts a parsimonious set of co-existing structures and estimates their abundances from structure profiling data. We demonstrate robust landscape reconstruction and quantitative insights into structural dynamics by analyzing numerous data sets. This work establishes a framework for data-directed characterization of structure landscapes to aid experimentalists in performing structure-function studies

Convolutional Dictionary Learning: Acceleration and Convergence

Convolutional dictionary learning (CDL or sparsifying CDL) has many applications in image processing and computer vision. There has been growing interest in developing efficient algorithms for CDL, mostly relying on the augmented Lagrangian (AL) method or the variant alternating direction method of multipliers (ADMM). When their parameters are properly tuned, AL methods have shown fast convergence in CDL. However, the parameter tuning process is not trivial due to its data dependence and, in practice, the convergence of AL methods depends on the AL parameters for nonconvex CDL problems. To moderate these problems, this paper proposes a new practically feasible and convergent Block Proximal Gradient method using a Majorizer (BPG-M) for CDL. The BPG-M-based CDL is investigated with different block updating schemes and majorization matrix designs, and further accelerated by incorporating some momentum coefficient formulas and restarting techniques. All of the methods investigated incorporate a boundary artifacts removal (or, more generally, sampling) operator in the learning model. Numerical experiments show that, without needing any parameter tuning process, the proposed BPG-M approach converges more stably to desirable solutions of lower objective values than the existing state-of-the-art ADMM algorithm and its memory-efficient variant do. Compared to the ADMM approaches, the BPG-M method using a multi-block updating scheme is particularly useful in single-threaded CDL algorithm handling large datasets, due to its lower memory requirement and no polynomial computational complexity. Image denoising experiments show that, for relatively strong additive white Gaussian noise, the filters learned by BPG-M-based CDL outperform those trained by the ADMM approach.Comment: 21 pages, 7 figures, submitted to IEEE Transactions on Image Processin