# Blind People: Clothing Category Classification and Stain Detection Using Transfer Learning
## 1 Introduction  
Vision is one of the senses that dominates our lives. It allows us to form perceptions of the surrounding world and give meaning to objects, concepts, ideas, and tastes [1]. Therefore, any type of visual loss can have a great impact on our daily routines, significantly affecting even the simplest tasks in our day-to-day habits. Vision loss can be sudden and severe, or the result of a gradual deterioration, where objects at great distances become increasingly difficult to see. Therefore, the wording \"vision impairment\" encompasses all conditions in which vision deficiency exists [2]. The individual who is born with the sense of sight and later loses it stores visual memories and can remember images, lights, and colors. This particularity is of the highest importance for re-adaptation. On the other hand, those who are born without the capacity of seeing can never form or possess visual memories. For both cases, clothing represents a demanding challenge. Recently, there has been an increasing focus on assistive technology for people with visual impairments and blindness, aiming at improving mobility, navigation, and object recognition [3; 4; 5]. Despite the high technology already available, some gaps remain, particularly in the area of aesthetics and image. The ways in which we dress and the styles that we prefer for different occasions are part of our identity [6]. Blind people do not have this sense, and dressing can be a difficult and stressful task. Taking advantage of the unprecedented technological advancements of recent years, it becomes essential to minimize the key limitations of a blind person when it comes to managing garments. Not knowing the colors, the types of patterns, or even the state of garments makes dressing a daily challenge. Moreover, it is important to keep in mind that blind people are more likely to have stains on their clothes, as they face more challenges in handling objects and performing simple tasks, such as eating, cleaning andpainting surfaces, and leaning against dirty surfaces, among others. In these situations, most of the time, when we involuntarily drop something on our clothes that causes a stain, we immediately attempt to clean it, as we know that the longer we take to clean it, the greater the difficulty in removing the stain later--something that might happen more often with blind people. Despite the already available cutting-edge technology and smart devices, some aspects of aesthetics and image still remain barely explored. This was the fundamental issue behind the motivation for this work--namely, how to enable blind people to feel equally satisfied with what they wear, functional, and without needing help. The scope of this research follows the previous work of the authors [7; 8; 9; 10], as, through image processing techniques, it is possible to help blind people to choose their clothing and to manage their wardrobes. In short, this work mainly contributes to the field with (i) the listing of relevant techniques used in image recognition for the identification of clothing items and for the detection of stains on garments; (ii) an annotated dataset of clothing stains, which could be later increased by new research; and (iii) a benchmark between different deep learning networks. The outcomes of this work are also foreseen to be implemented in a mobile application already identified as a preferred choice in a survey conducted with all departments of the Association of the Blind and Amblyopes of Portugal (ACAPO) [11]. Following the model approach already identified by the authors [12], the scope of the research presented here is focused on the algorithm for clothing category classification and stain detection. Alongside this, a mobile application and a mechatronic system, i.e., an automatic wardrobe, will complement all presented algorithms and methodology [13].