Image Analysis and Recognition by Aurélio Campilho, Mohamed Kamel

By Aurélio Campilho, Mohamed Kamel

The two-volume set LNCS 3211/3212 constitutes the refereed lawsuits of the foreign convention on photo research and popularity, ICIAR 2004, held in Porto, Portugal, in September/October 2004. The 210 revised papers offered have been conscientiously reviewed and chosen from 316 complete papers submitted. The papers are geared up in topical sections on photo segmentation, photograph processing and research, photo research and synthesis, photograph and video coding, form and matching, picture description and popularity, video processing and research, 3D imaging, photograph retrieval and indexing, morphology, biomedical functions, rfile processing, colour research, texture research, movement research, surveillance and distant sensing, monitoring, face detection and popularity, safeguard structures, visible inspection.

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We have applied such a post-processing, and found that OKMIS eliminates most of the noisy pixels – details of these experiments can be found in [10]. In addition to a nearly-noise-free foreground, OKMIS generates a larger foreground region, as we observe in Fig. 2, which is closer to the real spot foreground. Comparing OKMIS with SKMIS, the resulting foreground regions produced by the former are larger than those of the latter for all the images except for the first pair. Thus, in most of the cases, OKMIS results in much better results than SKMIS, even after the foreground correction process.

In this paper, we propose a modified NN Method which introduces a new filter for images on the neighboring planes. With this filter, the proposed method A. Campilho, M. ): ICIAR 2004, LNCS 3212, pp. 9–16, 2004. © Springer-Verlag Berlin Heidelberg 2004 10 K. Yano and I. Kumazawa separates the effect by light emission from planes in front of the target plane and that from planes behind the target plane. By separating these effects, the proposed method computes the image on the target plane more accurately than the conventional NN Method does.

Fig. 1. The arc stripe noise on the sector scan ultrasound images. In the following section, the analysis on the source of the arc stripe noise is presented in Section 2, the spatially adaptive filter is proposed in Section 3, and experimental examples are presented in Section 4. 2 Analysis on the Source of the Arc Stripe Noise This arc stripe pattern noise comes from the working mode of the steered sector scanner and wave propagation properties of the ultrasound beam. The ultrasound beam propagates as a longitudinal wave from the transducer surface into the propagation medium, and exhibits two kinds of beam patterns (as Fig.

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