Object Detection Methodologies for Blind People

Vision is the most important sense. Image plays vital role in the human perception of the surrounding environment. However there are visually impaired people, industry has created a variety of computer vision products and services by developing new electronic technologies for the blind in order to overcome the difficulties. Digital image processing is the field which processes the digital image by using digital computer. An increasing interest in developing technologies attempts to help visually impaired people in their daily lives. It is shown that the object identification is the difficult task for visually impaired people . Although there are many applications that can be used for this task, there are still limitations that require more improving. For this reason, this paper provides the survey and an analysis of various evaluations for the technologies that used in the object identification task. For the visually impaired the idea of sensory substitution can be used

A COMPARATIVE ANALYSIS OF OBJECT RECOGNITION SYSTEM USING SIFT,SURF AND FAST ALGORITHMS

Object recognition has always been an area of interest for various researchers since decades. In this paper an attempt has been made to give a comparison between various techniques of object recognition mainly feature based approaches. In this paper an overview of the Famous and impressive technique by David Lowe, which is Scale Invariant Feature Transform (SIFT) has been given. Another very important technique called Speeded-Up Robust Feature Transform (SURF) has been used to conclude with certain interesting results. FAST is the third technique which has also been discussed in this paper.  SIFT, SURF and FAST algorithms has been implemented on COIL dataset and a comparative analysis of these techniques has been given. The algorithms has been evaluated on two parameters i.e., number of features extracted and the time of execution. It has been seen that SIFT has detected more number of features as compared to SIFT and FAST. But the times of execution taken by SURF is comparatively less than SIFT and SURF

Approximate Matching in ACSM Dissimilarity Measure

AbstractThe paper introduces a new patch-based dissimilarity measure for image comparison employing an approximation strategy. It extends the Average Common Sub-matrix measure computing the exact dissimilarity among images. In the exact method, dissimilarity between two images is obtained by considering the average area of the biggest square sub-matrices in common between the images, by exact match of the extracted sub-matrices pixel by pixel. As an extension, the proposed dissimilarity measure computes an approximate match between the sub-matrices, which is obtained by omitting a controlled number of pixels at a given column offset inside the sub-matrices. The proposed dissimilarity measure is extensively compared with other well-known approximate methods for image comparison in the state-of-the-art. Experiments demonstrate the superiority of the proposed approximate measure in terms of execution time with respect to the exact method, and in terms of retrieval precision with respect to the other state-of-the-art methods

Sistema de detección y clasificación de peces utilizando visión computacional

La gestión de los recursos hidrobiológicos implica tanto el aspecto ecológico a través del equilibrio del ecosistema, como el aspecto económico mediante el control de la cantidad y calidad de los recursos pesqueros producidos en el Perú. En la actualidad, labores relacionadas a esta gestión son realizadas por empresas privadas y entidades del Estado como el Imarpe. La misión de estas es proteger la calidad de los recursos que llegan a los hogares de millones de peruanos. Esta investigación busca desarrollar un sistema para la detección, clasificación y, finalmente, la medición de diversas especies de peces, utilizando técnicas de visión computacional como el algoritmo SURF y redes neuronales convolucionales. Las pruebas, utilizando dos especies de peces, demostraron que la identificación alcanza un nivel de precisión del 90 % y que la clasificación alcanza una precisión del 80 %. Estos valores se obtienen bajo determinadas condiciones que se comentan en el desarrollo del artículo.The management of hydrobiological resources involves both the ecological aspect through the balance of the ecosystem, and the economic aspect through the control of the quantity and quality of the fishery resources produced in our country. Currently, work related to this management is carried out by private companies and state entities such as Imarpe. Their mission is to protect the quality of the resources that reach the homes of millions of Peruvians. This research aims to develop a system for the detection, classification and finally measurement of various species of fish, using computational vision techniques such as the SURF algorithm and convolutional neural networks. The tests, which used two fish species, showed that the identification reaches a 90% accuracy level and the classification reaches an 80% accuracy level. These values are achieved under certain conditions that are discussed in the article

Inclusive beauty: how buying and using cosmetics can be made more accessible for the visually impaired (VI) and blind consumer

Historically, assistive technologies for visually impaired and blind consumers evolved around aiding users in navigation, online content accessibility, learning, object and text recognition, and social interactions. There is no specific work done on technologies assisting these consumers with the use of cosmetics and engaging in self-grooming activities, whist such tasks are common and expected in the context of social and professional environments. This paper consists of two parts. The first one is a review of the assistive technologies relevant to shopping for cosmetics, as well as of the applications and systems which enable the choice of products, including some specifically developed for cosmetic purposes in line with the drive for personalised cosmetics. The second part reports the outcomes of a survey exploring the shopping and product usage of cosmetics by VI and blind individuals, including some qualitative data. The literature review identified a growing field of research and development of assistive technologies supporting shopping tasks and accessing product information. For example, conversion of text and visuals into auditory cues (verbal or other sounds) has been commonly used by VI and blind consumers. A small number of organisations/apps were found which provide advice, tutorials or direct assistance with cosmetics use and makeup application in particular. However, there were no reports of products and services within the remits of the cosmetic industry designed to assist the VI and blind users other than one brand adding Braille to product packaging. A range of technologies aimed at providing personalised cosmetic product choice were identified, however only one app was focused on helping such consumers with lipstick application. The survey showed that the VI and blind consumers used a variety of makeup products for reasons such as feeling good, looking professional, and simply because this is what sighted people do. Their choice of products was mostly driven by ease of use and brand familiarity, but sensory characteristics were also referred to. As lipstick was the most commonly used product, the colour was also an important choice factor. Shopping and finding the right product in store were considered easier than shopping online. The combination of primary and secondary data suggests that the use of cosmetics amongst VI and blind consumers could be encouraged in many ways: by improving the accessibility of product information – in store and online; by the design of accessible systems and applications which facilitate reliable product choice (colour and other desirable performance attributes); by offering access to affordable personalised products