Image retrieval using modified generic fourier descriptors

Generic Fourier Descriptors have been used for image retrieval [12]. In this paper, we have proposed a modification to the Generic Fourier Descriptors. We have performed experiments to compare the performance of the proposed method with the standard method. Tests were performed on Set B of the MPEG-7 Still Images Content Set [13]. The experimental results show the effectiveness of the proposed method.<br /

Kaedah pengesanan automatik salur darah retina untuk imej digital fundus

Retinaialahsatulapisanmembranyangterletakpadabelakangmatayangboleh menggambarkankeseluruhanimejsalurdarahmenggunakankamerafundus.Struktur salur darahpadaretinamampumemberikanpetunjukpentinguntukmengenalpasti penyakit-penyakityangberkaitanmatadanbadan.Penyakitberkaitanoftalmikdapat dibuktikan denganperubahandiameter,sudutpercabangan,dankekerintinganpada salur darahretina.Olehyangdemikian,prosessaringandigalakkan,namunbegitu pemeriksaanyangdilakukanadalahsecaramanualdanmemerlukankepakaran,masa, dan kosyangtinggikeranaperalatanyangcanggih.Suatukaedahpengesanansalur darah secaraautomatikdiperlukanuntukmendapatkanimejkeseluruhanrangkaian salur darahyanglebihefektifberbandingpengesanansecaramanual.Hasilnya, keseluruhanstruktursalurdarahretinadapatdikesandengancepatdantepat.Walau bagaimanapun,pengesanansalurdarahmerupakanprosesyangrumitkeranasalur darah retinamempunyairangkaiansalurdarahyangrumitdengankepelbagaiansaiz dan lebar.Selainitu,imejretinamempunyaihingar,kontrayangrendah,danvariasi kecerahanpadaimejyangsamamenyebabkansukaruntukmembezakansalurdarah dan latarbelakang.Kehadiranlingkarancakeraoptikpadaimejretinaperludiuruskan denganbaikkeranaiamerupakankawasanpalingcerahdanpembuluhdarahberasal daripadapusatnya.Objektifutamakajianiniadalahbagimembangunkankaedah pengesananautomatiksalurdarahretinauntukimejdigitalfundusyangcekap.Ia mampu mengesansalurdarahsecaraoptimumbermuladaripadalingkarancakera optik sehinggahujungstruktursalurdarah.Penyelidikaninimencadangkantigafasa utama, iaitupra-pemprosesan,segmentasirangkaiansalurdarah,danpasca pemprosesan. Fasapra-pemprosesaninimenyediakanimejretinayanglebihbaik berbanding imejasaluntukmeningkatkankontraantarasalurdarahretinadanlatar belakang. Seterusnya,fasakeduamerupakansegmentasirangkaiansalurdarah menggunakan modelberasaskangarispengesanansudut.Kaedahinidapatmengesan piksel yangmewakilisalurdarahberdasarkanpencirianyangtelahdilakukan.Akhir sekali, fasayangketigaialahfasapascapemprosesanyangterbahagikepadadua,iaitu pengesananpikseldanpenuraspikselberkepentingan.Prosespengesanandijalankan denganmenggunakankaedahheuristikdanOtsuterubah.Prosesinimenukarkanimej skala kelabukepadaimejperduaanbagipengesanansalurdarahretina,manakalabagi proses penuraspikselberkepentingan,iaterbahagikepadapenyingkirantitiktidak berkepentingandanmemperbaikipikselyanghilang.Prosesinidijalankandengan menggunakan sudutpengagihanhistogramuntukmenentukantaburanyangdiperoleh daripadapikselkejiranan.Maklumatinikemudiannyadigunakanuntuk menyingkirkanpikselhingardanmenyambungkanpikselyanghilangyangjuga merupakansebahagiandaripadasalurdarah.Dapatankajiantelahmembuktikan kaedah yangdicadangkanberjayamengesansalurdarahdenganmenunjukkan peningkatan ketepatanbagipangkalandataDRIVE,HRF,danSTAREiaitu masing-masing 95.58%,93.40%,dan94.90%.Berbandingkaedahterdahuluyang hanyamencatatkanketepatansebanyak94.15%dan93.24%bagipangkalandata DRIVE danSTARE.Kesimpulannya,kajianinitelahberjayamembangunkankaedah pengesananautomatiksalurdarahretinauntukimejdigitalfundus

Bag-of-Features Image Indexing and Classification in Microsoft SQL Server Relational Database

This paper presents a novel relational database architecture aimed to visual objects classification and retrieval. The framework is based on the bag-of-features image representation model combined with the Support Vector Machine classification and is integrated in a Microsoft SQL Server database.Comment: 2015 IEEE 2nd International Conference on Cybernetics (CYBCONF), Gdynia, Poland, 24-26 June 201

Intelligent robust control of high precision positioning systems using ANFIS

Modern mechanical systems, such as machine tools, microelectronics manufacturing equipment, are often required to operate in high speed to yield high productivity. At the same time, precision/accuracy requirement becomes more and more stringent because of factors like the reduced size of components in modern mechanical devices or microelectronics products and high-quality surface-finishing requirements. High Precision Positioning System (HPPS) usually requires a good control to satisfy the requirement: robust high accuracy positioning and tracking performance at high speed, fast response with no or small overshoot and robustness to uncertainties. The development of robust control systems for HPPS is an attempt to provide guaranteed stability despite uncertainties and disturbances associated with the plant. However, robust control techniques require a dynamic model of the plant under study and bounds on modeling uncertainty to develop control laws with guaranteed stability. Although identification techniques for modeling dynamic systems and estimating model parameters are well established, very few procedures exist for estimating uncertainty bounds. A conservative bound is usually chosen to ensure robust stability, which will severely affect the high performance requirement of HPPS

Study of object recognition and identification based on shape and texture analysis

The objective of object recognition is to enable computers to recognize image patterns without human intervention. According to its applications, it is mainly divided into two parts: recognition of object categories and detection/identification of objects. My thesis studied the techniques of object feature analysis and identification strategies, which solve the object recognition problem by employing effective and perceptually important object features. The shape information is of particular interest and a review of the shape representation and description is presented, as well as the latest research work on object recognition. In the second chapter of the thesis, a novel content-based approach is proposed for efficient shape classification and retrieval of 2D objects. Two object detection approaches, which are designed according to the characteristics of the shape context and SIFT descriptors, respectively, are analyzed and compared. It is found that the identification strategy constructed on a single type of object feature is only able to recognize the target object under specific conditions which the identifier is adapted to. These identifiers are usually designed to detect the target objects which are rich in the feature type captured by the identifier. In addition, this type of feature often distinguishes the target object from the complex scene. To overcome this constraint, a novel prototyped-based object identification method is presented to detect the target object in the complex scene by employing different types of descriptors to capture the heterogeneous features. All types of descriptors are modified to meet the requirement of the detection strategy’s framework. Thus this new method is able to describe and identify various kinds of objects whose dominant features are quite different. The identification system employs the cosine similarity to evaluate the resemblance between the prototype image and image windows on the complex scene. Then a ‘resemblance map’ is established with values on each patch representing the likelihood of the target object’s presence. The simulation approved that this novel object detection strategy is efficient, robust and of scale and rotation invariance

Coherence based histograms for shape retrieval

Histograms have been used for Shape Representation and Retrieval. The drawback of the histograms method is that histograms can be same for dissimilar shapes, which renders the method less effective for retrieval of shapes. In this paper, we describe the concept of coherence. We show how coherence can be used with distance and angular histograms. We perform experiments to test the effectiveness of the proposed method. It is found that coherence improves accuracy of retrieval significantly.<br /