Analisis dan Implementasi Image Retrieval Menggunakan Stochastic Paintbrush Transformation (SPT)

ABSTRAKSI: Pada tugas akhir ini image retrieval khususnya Content-Based Image Retrieval (CBIR) dikembangkan menggunakan metode Stochastic Paintbrush Transformation (SPT), yaitu suatu algoritma baru untuk transformasi citra kedalam representasi lukisan (paintbrush). Algoritma SPT dipilih karena metode ini bersifat otomatis, mampu menginterpretasikan citra, dan mampu menangkap konten visual dari suatu citra. SPT melakukan ekstraksi citra didasarkan pada representasi lukisan dari citra asli yaitu melalui fitur paintbrush stroke parameter yang terdiri dari bentuk dan ukuran brush, warna, orientasi dan lokasi. TA ini dibagi menjadi dua subsistem. Pertama subsistem penyimpanan data, yaitu melakukan ekstraksi fitur paintbrush citra dan menyimpannya kedalam database. Kedua subsistem pencarian citra query, hasil ekstraksi fitur paintbrush citra query dibandingkan dengan fitur paintbrush semua citra database, hasil akhir berupa sejumlah N citra database yang memiliki beberapa tingkat kemiripan dengan citra query. Pengukuran kemiripan citra didapat dari proses similarity berdasarkan parameter warna, orientasi dan lokasi brush. Hasil analisis yang didapat adalah penggunaan metode SPT dalam sistem CBIR menghasilkan performansi sistem yang baik tetapi membutuhkan waktu transformasi citra yang cukup lama.Kata Kunci : image retrieval, Content-Based Image Retrieval (CBIR), Stochastic Paintbrush Transformation (SPT), paintbrush stroke parameter, brush, orientasi, similarity.ABSTRACT: This final project describes a new method to develop image retrieval, especially in Content-Based Image Retrieval (CBIR), called Stochastic Paintbrush Transformation (SPT). It is an algorithm to transform the image into a painting representation (paintbrush). SPT is chosen because it is completely automatic and it also can provide an interpretation of an image and capture its visual content. The image extraction on SPT is based on painting representation of the original image by using paintbrush stroke parameter features which includes shape, size, color, orientation, and location of the brush. This final project is divided into two subsystems. The first is data storage subsystem, which extracts the image paintbrush stroke features and store them into the database. Second, the query image retrieval subsystem matches the resulting paintbrush features of the query image and the resulting paintbrush features of all images from the database. This process results in N number of the database images which have some similarity levels to the query image. The similarity measurement of an image is obtained from similarity process based on color, orientation, and location parameter of the brush. Experimental analysis results show that the SPT method in CBIR system has a good performance system but not so good in image time transformation.Keyword: image retrieval, Content-Based Image Retrieval (CBIR), Stochastic Paintbrush Transformation (SPT), paintbrush stroke parameter, brush, orientation, similarity

Analisis dan Implementasi Image Retrieval Menggunakan Sorted Gray Level Polynomial Curve

ABSTRAKSI: Dengan semakin berkembangnya teknologi informasi telah banyak dikembangkannya berbagai metode pencarian content based, misalnya sistem Content Based Image Retrieval (CBIR) yang merupakan mekanisme pencarian query citra, ini disebabkan pencarian citra berdasarkan text sudah tidak efektif lagi. Pada tugas akhir ini, image retrieval yang dibangun dikembangkan dengan metode sorted gray level histogram polynomial curve. Dimana untuk mendapatkan nilai fitur citra digunakan persamaan polinomial dari histogram yang terurut. Derajat persamaan polinomial yang digunakan mulai dari derajat 1 sampai derajat 10, dan dipilih derajat mana yang memiliki nilai error terkecil sebagai fitur citra. Fitur citra yang dihasilkan berupa n+1 koefisien dari persamaan polinomial derajat n dengan nilai error terkecil. Perhitungan similarity antara citra query dengan citra di database menggunakan euclidean distance. Hasil dari tugas akhir ini adalah sebuah sistem CBIR yang dapat digunakan dalam proses pencarian citra dan dapat menganalisis seberapa akuratkah sitem CBIR jika menggunakan metode sorted gray level histogram polynomial curve sebagai pengekstrakan fitur citra.Kata Kunci : Content Based Image Retrieval, sorted histogram, polynomial curvesABSTRACT: With growing information technology has been widely developed various content-based searching method, i.e. Content-Based image retrieval (CBIR) systems, which is a mechanism for query image searches, image searches due based on the text is not effective. In this final project, which was built image retrieval method was developed by sorted gray level histogram polynomial curve. Whereby to obtain the value of the image features used polynomial equation of the sorted histogram. Degree of polynomial equation that are used from degree 1 to degree 10, and selected degree which has the smallest error as the image feature. Features generated image of n +1 coefficients of the polynomial degree n with the smallest error. The calculation of similarity between the query image with images in the database using Euclidean distance. The results of this final project is a CBIR system that can be used in image search process and can analyze how accurate is if the CBIR system using sorted gray level histogram polynomial curve as image features extraction.Keyword: Content Based Image Retrieval, sorted histogram, polynomial curve

Doctor of Philosophy

dissertationElectron microscopy can visualize synapses at nanometer resolution, and can thereby capture the fine structure of these contacts. However, this imaging method lacks three key elements: temporal information, protein visualization, and large volume reconstruction. For my dissertation, I developed three methods in electron microscopy that overcame these limitations. First, I developed a method to freeze neurons at any desired time point after a stimulus to study synaptic vesicle cycle. Second, I developed a method to couple super-resolution fluorescence microscopy and electron microscopy to pinpoint the location of proteins in electron micrographs at nanometer resolution. Third, I collaborated with computer scientists to develop methods for semi-automated reconstruction of nervous system. I applied these techniques to answer two fundamental questions in synaptic biology. Which vesicles fuse in response to a stimulus? How are synaptic vesicles recovered at synapses after fusion? Only vesicles that are in direct contact with plasma membrane fuse upon stimulation. The active zone in C. elegans is broad, but primed vesicles are concentrated around the dense projection. Following exocytosis of synaptic vesicles, synaptic vesicle membrane was recovered rapidly at two distinct locations at a synapse: the dense projection and adherens junctions. These studies suggest that there may be a novel form of ultrafast endocytosis

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

Excellentia Eminentia Effectio

"In these pages you will learn about the fascinating research endeavors that each of our faculty members is undertaking. We have divided their research into the broad categories of health, sustainability, information, and systems. While we recognize the imperfect nature of categorizing research that, by its very nature may be interdisciplinary or transdisciplinary, we nonetheless believe it will be helpful as a way to see the depth and breadth of our research endeavors within each grouping. As you read the profiles on these pages, I know you will begin to appreciate that, taken as a whole, the research spectrum at Columbia Engineering is exceptional and that, as our professors go about their work, they are at the cusp of making breakthroughs that will have a major impact on the way we live our lives today and tomorrow.

Investigating the relations between object affordance and perception using behavioural and neuroimaging experiments

Previous research has shown facilitatory effects on attention and perception when object pairs are positioned for action compared to when they are not positioned for action. The present thesis aimed to better understand the mechanisms underlying this paired-object affordance effect. Chapters 2 and 3 showed that different but interacting parieto-frontal networks contribute to the effects of paired-object affordance in healthy participants. Chapters 4 and 5 explored the effects of paired-object affordance on visual extinction; the data showed that recovery from extinction was sensitive to the familiarity of the object pair and the completeness of the active object rather than the passive object within an interacting pair. Finally, the role of contextual information and task demands on the automatic perception of paired-object affordance effects was directly explored. The results indicate that only explicit but not implicit task demands (searching for an action vs. a colour pair, respectively) had facilitatory effects on performance and that semantic information in a scene also modulates the automatic perception of paired-object affordance. The findings provide novel behavioural and neuroimaging evidence that paired-object affordance is influenced by contextual information and task demands, with the active object (the tool) within a pair modulating the allocation of attention