Browsing by Author "Andrade Rodas, Juan Manuel"

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    Determinación de la cobertura del sistema CDMA 450
    (2008) Albarracín, Freddy M.; Velecela M., Jorge F.; Andrade Rodas, Juan Manuel
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    Diseño de un edificio inteligente
    (2012) Orbe Astudillo, Marcos Humberto; Andrade Rodas, Juan Manuel
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    Diseño de un sistema telemático de visualización de información en carreteras y centros poblados
    (2009) Rockwood Iglesias, Jhon Paul; Andrade Rodas, Juan Manuel
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    Diseño de una red de fibra óptica Gpon aplicado al cantón Gualaceo para la empresa eléctrica regional Centrosur C.A.
    (2009) Carpio Garay, Edison Fernando; Morocho Chicaiza, Walter Geovanny; Andrade Rodas, Juan Manuel
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    Diseño de una red GSM para los cantones de: Cuenca, Paute, Gualaceo, Chordeleg, Girón y Santa Isabel
    (2002) Pinos Espinoza, Hugo Alejandro; Urdiales Flores, Luis Eduardo; Andrade Rodas, Juan Manuel
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    Evaluación de métodos de corrección radiométrica y geométrica de una cámara de campo de visión amplio
    (Universidad de Cuenca, 2025-09-24) Palaguachi Dután, Felipe Sebastián; León Guanoquiza, Franklin Josué; Andrade Rodas, Juan Manuel; Palacio Baus, Kenneth Samuel
    This work evaluates the application of geometric and radiometric correction techniques on sky images captured with wide-field cameras, with the aim of mitigating distortions introduced by wide-angle lenses (140° and 180°) and improving the quality of these images for analysis in computer vision. The main objective of this work is to obtain accurate representations of sky conditions, which are essential for applications such as short-term photovoltaic forecasting. A comprehensive review of the state of the art is presented, exploring geometric models such as Kannala-Brandt, Scaramuzza, UCM, EUCM, and Mei, as well as radiometric methods including HDR image generation using Debevec, Mitsunaga, and Robertson techniques, including vignetting correction using approaches by Gao, Lopez-Fuentes, and Zheng. Comparative experiments have been designed to evaluate the performance of these methods on synthetic and real images, using metrics such as PSNR, SSIM, RPE, and radiometric uniformity. The results highlight that the Kannala-Brandt model excels in the correction of synthetic images, while EUCM and Mei offer greater accuracy in real scenarios; in the radiometric domain, the Debevec technique preserves key HDR details, and the Lopez-Fuentes method optimizes vignetting correction. Finally, the implications of these findings for sky image enhancement are discussed, and future lines of research are proposed, such as the development of hybrid models and the expansion of datasets, with an independent focus on their application for photovoltaic prediction studies.
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    Impact of electrical energy efficiency programs, case study: food processing companies in Cuenca, Ecuador
    (2014-04-01) Carrillo Rojas, Galo José; Andrade Rodas, Juan Manuel; Barragán Escandón, Edgar Antonio; Astudillo Alemán, Ana Lucía
    This exploratory study illustrates the effects of the application of electrical energy efficiency programs in 7 food processing companies in Cuenca, Ecuador. The research encompassed phases of diagnosis, intervention and evaluation. A comparative analysis between the companies was conducted: energy consumption versus product volume, energy-quality analysis, relation between compliance/specific energy consumption, and the impact on CO2 emissions. Results revealed that the acceptance to the recommendations of savings is biased by the level of investments and the willing/proneness of the administration. The study showed that interventions had a partial effect on the reduction of the specific energy consumption in 4 companies. In addition, it has obtained a positive effect on the power factor correction in one company and an improvement on the load balance in 5. The research showed the existence of a significant reduction of emissions post-intervention, highlighting the effectiveness of the programs. © The authors; licensee Universidad Nacional de Colombia.
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    No-Reference Image Sharpness Assessment Based on Perceptually-Weighted Image Gradients
    (IEEE, 2023) Andrade Rodas, Juan Manuel; Andrade Rodas, Juan Manuel
    The fact that human visual perception is highly spe-cialized for extracting structural information has been efficiently exploited in full-reference image quality assessment algorithms; additionally, it has been shown that the human perception of sharpness depends on the local image contrast. Since the image gradients can measure effectively the image structure, we propose a training-free no-reference objective image sharpness assessment method based on the statistical analysis of perceptually-weighted normalized -gradients of relevant pixels in the input image. Results over six subject-rated publicly available databases show that the proposed no-reference sharpness assessment algorithm correlates well with perceived sharpness and provides competitive performance when compared with state-of-the-art algorithms despite its low computational burden.
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    Robust radial distortion corection based on alternate optimization
    (IEEE, 2016) Andrade Rodas, Juan Manuel
    A robust radial distortion correction method that requires only a single image of the distorted imaged pattern is presented. The method is robust to the orientation of the imaged pattern and does not require the availability of the ideal reference reg- ularly structured pattern which can be recreated from detected features in the distorted image. Radial distortion parameters, i.e., the Center of Distortion (CoD) and radial distortion coefficients (RDC), are optimized by minimizing corresponding cost functions in an alternate manner. Tests with synthetic and real data are presented in order to illustrate the performance robustness of the proposed algorithm.
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    Sharpness enhancement of stereo images using a depth-based per-pixel regularization
    (IEEE, 2021) Andrade Rodas, Juan Manuel; Andrade Rodas, Juan Manuel
    Blur is one of the causes of visual discomfort in stereopsis. The application of 2D image sharpening algorithms to the left and right view can produce an interdifference which causes eyestrain and visual fatigue for the viewer. Additionally, it has been shown, through subjective tests, that the perception of sharpness is affected by depth. A 3D sharpness enhancement method for stereo images that incorporates binocular vision cues as well as depth information is presented. The proposed algorithm decomposes each of the input stereo images into a base and a detail layer. The visibility thresholds maps given by the Binocular Just Noticeable Difference (BJND), which include binocular mechanisms such as luminance and contrast masking are used as guidance maps in the computation of the base layer; additionally, the depth of objects in the scene is used to provide a per-pixel depth-weighted regularization to the computation of the base layer. The detail layer, defined using the input images and the computed base layer is boosted and then added to the base layer to provide the final sharpness enhanced images. The proposed sharpness enhancement method results in a low interdifference error of corresponding positions of the stereo pair and in an enhanced subjective visual quality. Comparative quantitative results in terms of interdifference using a publicly available dataset show that the proposed algorithm outperforms state-of-the-art algorithms. Qualitative and subjective evaluation results are also included in order to show the perceived visual quality improvement provided by the proposed algorithm.